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Competitive Sourcing:
Implementation Will Be Key to Success of New Circular A-76
GAO-03-943T: Published: Jun 26, 2003. Publicly Released: Jun 26, 2003.
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In May 2003, the Office of Management and Budget (OMB) issued a new Circular A-76--which sets forth the government's competitive sourcing process. Determining whether to obtain services in-house or through commercial contracts is an important economic and strategic decision for agencies, and the use of A-76 is expected to grow throughout the federal government. In the past, however, the A-76 process has been difficult to implement, and the impact on the morale of the federal workforce has been profound. Moreover, there have been concerns in both the public and private sectors about the timeliness and fairness of the process and the extent to which there is a "level playing field" for conducting public-private competitions. It was against this backdrop that the Congress enacted legislation mandating a study of the government's competitive sourcing process, which was carried out by the Commercial Activities Panel, which was chaired by the Comptroller General of the United States. This testimony focuses on how the new Circular addresses the Panel's recommendations with regard to providing a better foundation for competitive sourcing decisions, and the challenges agencies may face in implementing the new A-76.
Overall, the new Circular is consistent with the principles and recommendations that the Commercial Activities Panel reported in April 2002, and should provide an improved foundation for competitive sourcing decisions in the federal government. In particular, the new Circular permits greater reliance on procedures in the Federal Acquisition Regulation--which should result in a more transparent and consistently applied competitive process--as well as source selection decisions based on tradeoffs between technical factors and cost. The new Circular also suggests potential use of alternatives to the competitive sourcing process, such as public-private and public-public partnerships and high-performing organizations. The new Circular should result in increased savings, improved performance, and greater accountability. However, this initiative is a major change in the way the government operates, and implementing the new Circular A-76 will likely be challenging for many agencies. A major challenge agencies will face will be meeting a 12-month limit for completing the standard competition process. This provision aims to respond to complaints about the length of time taken to conduct A-76 cost comparisons. However, GAO studies of competitive sourcing at the Department of Defense (DOD) have found that competitions can take much longer than 12 months. Other provisions in the new Circular may also prove burdensome in implementation. Lessons learned by DOD and other agencies as they initiate efforts to improve acquisition, human capital, and information technology management could prove invaluable as agencies implement the new A-76 provisions--especially those that demonstrate best competitive sourcing practices. Successful implementation of the Circular's provisions will also likely require additional financial and technical support and incentives.
Oct 7, 2015
National Protection and Programs Directorate:Factors to Consider when ReorganizingGAO-16-140T: Published: Oct 7, 2015. Publicly Released: Oct 7, 2015.
Oct 5, 2015
U.S. Postal Service:Actions Needed to Make Delivery Performance Information More Complete, Useful, and TransparentGAO-15-756: Published: Sep 30, 2015. Publicly Released: Oct 5, 2015.
Sep 30, 2015
Managing for Results:Implementation of GPRA Modernization Act Has Yielded Mixed Progress in Addressing Pressing Governance ChallengesGAO-15-819: Published: Sep 30, 2015. Publicly Released: Sep 30, 2015.
Sep 23, 2015
Regulatory Guidance Processes:Agencies Could Benefit from Stronger Internal Control PracticesGAO-15-834T: Published: Sep 23, 2015. Publicly Released: Sep 23, 2015.
Sep 16, 2015
Federal User Fees:Key Considerations for Designing and Implementing Regulatory FeesGAO-15-718: Published: Sep 16, 2015. Publicly Released: Sep 16, 2015.
Sep 10, 2015
Managing for Results:Greater Transparency Needed in Public Reporting on the Quality of Performance Information for Selected Agencies' Priority GoalsGAO-15-788: Published: Sep 10, 2015. Publicly Released: Sep 10, 2015.
Sep 3, 2015
Capitol Power Plant:Architect of the Capitol Should Update Its Long-term Energy Plan before Committing to Major Energy ProjectsGAO-15-436: Published: Sep 3, 2015. Publicly Released: Sep 3, 2015.
Aug 10, 2015
Federal Supply Schedules:More Attention Needed to Competition and PricesGAO-15-590: Published: Jul 9, 2015. Publicly Released: Aug 10, 2015.
Aug 7, 2015
Federal Real Property:GSA Needs to Determine Its Progress toward Long-term Sustainability of Its PortfolioGAO-15-609: Published: Jul 15, 2015. Publicly Released: Aug 7, 2015.
Jul 29, 2015
DATA Act:Progress Made in Initial Implementation but Challenges Must be Addressed as Efforts ProceedGAO-15-752T: Published: Jul 29, 2015. Publicly Released: Jul 29, 2015.
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Chelsea Collins, a sixth-grade language arts teacher at Woodstown Middle School in the Woodstown-Pilesgrove School District in Salem County, has been named the 2015-16 New Jersey State Teacher of the Year.
The State Board of Education today adopted a recommendation by Commissioner of Education David Hespe to move Jersey City's public schools one step closer to local control. Jersey City, which has been under state control for 26 years, longer than any other district in New Jersey, has been moving toward regaining full local control in recent years. Having already regained the right to local governance and management of its own budget, the district was today granted control over personnel and operational decisions as well.Read
NJEA member Maryann Woods-Murphy, a Gifted and Talented Specialist at Nutley Public Schools in Nutley, NJ, has been named to the NEA Foundation Board of Directors. Woods-Murphy was the 2009-10 New Jersey Teacher of the Year. She joins five other new board members, each serving a three-year term.Read
Thanks to a new law, New Jersey teachers will be able to earn a teacher leader endorsement to their instructional certificates. Teacher leadership provides a model for schools that will allow teachers to lead from their classrooms. Teacher leaders are not doing the job of administrators; they will be advocates for the profession and student learning. They will serve in positions where they help improve teacher practice and create a collaborative culture where decisions about schools and learning can be made with teachers, not above them.Read
Here you'll find the NJEA News Service – a service dedicated to providing information about New Jersey's public schools to journalists, elected officials, opinion leaders, public school parents and New Jersey resident; as well as information about NJEA and media contacts.
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Critics would like the public to believe that New Jersey's public school system is broken and is failing the students, but here's the simple truth: Our public schools work. In fact, according to a leading annual publication, New Jersey's public schools are truly the best in the nation.
The NJEA Reporter was published from 1944 to 1949 and from 1963 to 2014, when it merged with the NJEA Review. It focused on Association events and priorities such as collective bargaining, legislative actions, Member Benefits, and NJEA conferences and workshops. The NJEA Reporter also highlighted the actions of NJEA's local and county associations.
Published since 1927, the NJEA Review is the Association's professional journal. The magazine is published monthly September through May. It shares information on professional issues and offerings, highlights members' professional accomplishments and programs, and offers tools for professional growth.
Your NJEA membership card is your ticket to discounts on merchandise, insurance, entertainment, travel, and personal legal services.

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The football team put on the pads for the first time this spring, practicing for two hours on Wednesday on the Thomas-Drew Practice Fields. The practice was the third of the season for the Crimson Tide.
Click here for the original story.
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AHMEDABAD: Gujarat chief minister Narendra Modi was leading in Maninagar constituency.
At the end of first round of counting, Modi is way ahead of his Congress rival Shweta Bhatt. Modi has polled 8780 votes, while Bhatt has got 1015 votes, state election office sources said.
State Congress chief Arjun Modhwadia is trailing his BJP rival in Porbandar, while Gordhan Zadafia, general secretary of Gujarat Parivartan Party is also behind his BJP rival in Gondal.
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Proposition B has both sides howling.
The ballot proposal, which Missouri voters will consider next Tuesday, would require large-scale dog breeding operations to provide sufficient care for animals, ban operators from having more than 50 breeding dogs and create a misdemeanor for violations.
Animals rights groups petitioned to put the measure before voters. A simple majority is required for passage.
Supporters of Proposition B maintain that existing laws are not adequate and that new regulations are needed to end what they call Missouri's reputation as being the "puppy mill capital" of America.
"Current Missouri law has not been sufficient in stopping puppy mills," said Jeane Jae of the Humane Society of Missouri, which urges passage of Proposition B. "We are not opposed to commercial dog breeding. We are opposed to substandard puppy mills that aren't taking care of their animals."
Opponents say existing rules are sufficient for law-abiding breeders and worry that there's a hidden agenda behind the proposition that could lead to greater government regulation of farm animals.
"This only targets those who are licensed and legal and abiding by current laws," said Karen Strange of the Missouri Pet Breeders Association, which urges defeat of Proposition B. "This will have a lot of unintended consequences. Among those is the elimination of legal breeders while doing nothing to stop illegal operations."
While the ballot language deals with dogs, opponents fear the measure could open the door to strict controls of livestock farms and the agriculture industry.
Strange said the Humane Society of Missouri has "a proven track record" of support for increased rigidity when it comes to animal care laws. She said many people, especially those in urban areas, do not "understand the animal rights movement and its threat."
"I know what they're up to," said Strange, who has been involved in the debate for two decades.
Jae said supporters have no hidden agenda, and that it's "absurd" to think that Proposition B would lead to anything else. Jae has been on many rescues at substandard kennels over the last six years and said it's "heartbreaking that those animals are forced to live in" such conditions.
"This proposition has nothing to do with livestock agriculture," Jae said. "It has everything to do with dogs in large commercial facilities, and that's it."
The state estimates that government entities would experience a one-time cost of almost $655,000 if Proposition B passes, and ongoing costs of more than $520,000.
Missouri's 1,449 commercial dog breeders already must have both federal and state licenses, and their facilities are subject to regular inspections. The site reviews generally are done once a year.
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Marriott's Shadow Ridge
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TravelPod Member ReviewsMarriott's Shadow Ridge Palm Desert
Love spending time here. Great timeshare resort with a great golf course. The staff is very welcoming. Great activities both on and off the resort
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Trip #11 2014
Annual visit to Palm Desert, CA. Our 8th or 9th trip. The last 3 have been two week trips. After a 2 1/2 hour ride we arrived at Shadow Ridge for our two week stay. We were given our first choice of accommodations. Top floor building 2700 with a view of the 16th hole. We ate dinner at SiBon's a favorite restaurant we discovered last year. Belgium …
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Front of pack food labels or signpost labels are currently widely discussed as means to help consumers to make informed food choices. It is hoped that more informed food choices will result in an overall healthier diet. There is only limited evidence, as to which format of a food label is best understood by consumers, helps them best to differentiate between more or less healthy food and whether these changes in perceived healthiness result in changes of food choice.
In a randomised experimental study in Hamburg/Germany 420 adult subjects were exposed to one of five experimental conditions: (1) a simple "healthy choice" tick, (2) a multiple traffic light label, (3) a monochrome Guideline Daily Amount (GDA) label, (4) a coloured GDA label and (5) a "no label" condition. In the first task they had to identify the healthier food items in 28 pair-wise comparisons of foods from different food groups. In the second task they were asked to select food portions from a range of foods to compose a one-day's consumption. Differences between means were analysed using ANOVAs.
Task I: Experimental conditions differed significantly in the number of correct decisions (p < 0.001). In the condition "no label" subjects had least correct decisions (20.2 ± 3.2), in the traffic light condition most correct decisions were made (24.8 ± 2.4). Task II: Envisaged daily food consumption did not differ significantly between the experimental conditions.
Different food label formats differ in the understanding of consumers. The current study shows, that German adults profit most from the multiple traffic light labels. Perceived healthiness of foods is influenced by this label format most often. Nevertheless, such changes in perceived healthiness are unlikely to influence food choice and consumption. Attempts to establish the informed consumer with the hope that informed choices will be healthier choices are unlikely to change consumer behaviour and will not result in the desired contribution to the prevention of obesity and diet related diseases.
Overweight and obesity are an increasing problem. Worldwide more than 1,6 billion people (age 15+) are overweight, and approximately 400 million adults are obese [1]. Germany is one of the countries with the highest prevalence of overweight among adults (BMI >25) in the European Union [2]. The German Child and Adolescent Health Survey (KiGGS) has demonstrated that overall 15% of children and adolescents between the ages of 3 and 17 are overweight, and 6.3% suffer from obesity [3,4]. This represents a 50% increase in the prevalence of overweight and more than 100% increase in the prevalence of obesity as compared to the BMI reference data from 1985–1999 [5]. Recently, the German National Nutrition Survey II (NVS II) [6] a representative survey on the nutrient and energy intake of 14–80-year-olds determined that one in five Germans is obese (BMI ≥ 30). Analyses on current food consumption, lifestyle and eating behaviour demonstrated that 36% men and 31% women exceeded the guidelines for daily energy intake for median physical activity. Of even more concern are the results for the daily fat intake: 80% men and 76% women exceed the daily fat intake recommendations (30% of total energy intake) [7]. In almost the same manner eating habits have changed worldwide leading to an increased consumption of pre-packed food generally containing high levels of sugar, fat, saturated fatty acids, trans-fatty acids and sodium [8]. To prevent nutrition related diseases the WHO has recommended to reduce these nutrients in order to improve the nutritional value [9]. Hence consumer interests in health and diet issues have increased and consequently nutrition labelling has received considerable attention. Interpretational aids can help consumers to appraise the nutrient contribution of specific foods to the overall diet enabling informed consumer choices, leading to the consumption and consequently to the production of healthier products [10-12]. However, research on nutrition information on packed foods showed that the given information is often misinterpreted, confusing and inappropriate for estimating an individual product's contribution to the overall diet [11,13,14]. Adding some kind of benchmark either numerical or non-numerical seems to help [11,12]. Label use is affected by education, gender, age and time pressure, i.e., consumers search for nutrition-related information as long as the costs (time and/or price) will not outweigh the benefits [14].
In addition to the customary back-of-pack labelling formats, several food manufactures are using signposts on the front of the packages to help consumers interpret the nutritional information. Signposts could probably change eating patterns by informing and supporting consumers to make healthy choices. However, the effectiveness of such labelling depends on the organisation and presentation of the information, implying the importance of regulatory issues [10].
In Europe nutrition labelling is compulsory if a nutrition claim is made. Depending on the nutrition claim either the contents of energy, protein, carbohydrate and fat (so called "big 4") or these four plus sugars, saturated fat, fibre and sodium.(so called "big 8) have to be detailed [15,16]. Due to the lack of binding agreements, there is no European standard guideline on front-of-pack or signpost labelling regulations. Nevertheless, several signpost labels have already been developed although their effect on consumers is highly controversial.
Examples of detailed labels are the 'Guideline Daily Amounts' (GDA) showing the total amount of energy and nutrients as a percentage of what a typical healthy adult should be eating daily on the basis of a 2000 kcal diet. The traffic light-labels (simple or multiple) give information on the level (i.e. high, medium or low) of individual nutrients in the product using the colour coding red, amber or green. The colour coded GDA combines the two previous label systems. Studies on behalf of the UK Food Standard Agency showed that the colour coded labels like the multiple traffic-light and coloured GDA formats are most accepted and well understood by consumers [17-19].
Results from a UK market study on food labels indicated a high awareness of both, GDA and traffic light label systems. In terms of understanding, the GDA concept is good. The understanding of the traffic light concept seems to be characterised by some exaggeration of the meaning of the colours [20].
More or less simple labels are the health logos "pick the tick" in Australia and New Zealand, a tick symbol for approved foods low in total fat, saturated fat, added sugar and sodium, and the "smart spot" in the USA for products meeting similar nutrition criteria [21-23]. In the Netherlands criteria for "the healthy choice" logo, a single tick on the front of the package are derived from WHO standards of trans fat, saturated fat, sugar and sodium [24].
Research on consumers' use of various formats of nutrition labels has been mainly undertaken by consumer associations, major retailers and the Food Standards Agency, focusing on the liking of various signpost labels [25]. In general, most customers like the idea of front-of-pack signposting as a shopping aid. In addition most consumers state that they understand the information provided by these labels, which may be characterised as perceived or subjective understanding. However, there is virtually no insight into how labelling information will be used in a real-world shopping situation and how it will affect consumers' dietary patterns. Research to evaluate differences in the consumers' objective (actual) and subjective (perceived) understanding of various label formats is still to come [25]. Only a few studies investigated the effect of different formats on behavioural change [20,21,26]. This makes it difficult to identify the everyday use of (different) nutrition labels and their influence on diet quality.
The objective of this research was to investigate which signpost food label format enables consumers best to differentiate healthier products from less healthy ones and to examine the impact of these food labels on the food choice and quality of diet.
Study design and experimental conditions
A randomized experimental study was conducted using 5 experimental conditions representing different label formats. Four different label formats (signposts) were examined (see figure 1). The study protocol has been approved by the ethical committee of the Life Sciences Faculty of the Hamburg University of Applied Sciences.
Figure 1. The nutrition labelling formats (a) simple tick; (b) traffic light format; (c) monochrome Guideline Daily Amount (GDA); (d) colour-coded GDA (CGDA). Translation Figure 1. 1.a) "eat healthy – stay healthy". Portion size (approx. 1 glass) is 200 ml. a-d) one portion (approx. 1 glass) is 200 ml. b-d) wenig: low; mittel: medium; viel: high; Kalorien: calories; Fett: fat; gesättigte Fettsäuren: saturated fatty acids; Zucker: sugar; Natrium: sodium. 1.c) each portion (200 ml/approx. 1 glass) contains xx% of your guideline daily amount. 1.d) each portion (20 gm/approx. 1 Tablespoon) contains xx% of your guideline daily amount.
Materials/food cards
Foods from different food categories were photographed, and the photos printed in postcard size. All food pictures were presented unbranded to the participants. In the experimental condition with the food label signpost, this was located below the product as was the information about the portion size (see figure 1). In the experimental condition without the signpost only the portion size was presented below the picture. If nutrition facts were available for the reference food (e.g. front-of-pack nutrition labelling, website information, requested information via telephone or email) this data was taken and adapted to the different labels. If product information was not available the ingredients were calculated in accordance with the technical guidelines using nutrient content tables or computerized nutrition content programmes for similar products [27-30].
Food Label formats
1. A simple healthier choice tick (tick), similar to the Dutch "Ik kies bewust", the American "smart choices" or the "pick the tick" logo of New Zealand's National Heart foundation was given, if the food qualified for the green colour, for each, sugar, fat, saturated fat and sodium in the multiple traffic light system. For foods which did not meet the criteria no logo, but only portion size was shown. Thus the "tick" label represents a combined evaluation of the food's nutrient content, whereas the other label formats give separate evaluations for the different nutrients.
2. In the multiple traffic light label system (t-l) the corresponding colour for the content of fat, saturated fat, sugar and sodium were given. Green, amber and red represent low, moderate and high contents of the nutrients in the food product, respectively. The colours are based on concentration in grams per 100 g or per 100 ml and the criteria of the UK Food Standards Agency were applied to assign the colour codes [31]. In addition calories were shown in neutral colour (white/grey).
3. The Guideline Daily Amount (GDA) labels showed the amount of fat, saturated fat and sugar and sodium in grams as well as the kilocalories per portion and the percentage of each of these ingredients according to the "Guideline Daily Amount for women" [32].
4. The colour Coded GDA labels (CGDA) were similar to the GDA labels. In addition to the specified amounts of nutrients a green, amber or red colour symbol analogue to the traffic light criteria was given.
5. As an additional experimental condition we used "no label" where the foods were shown only with portion size information without any additional label.
For all five experimental conditions foods were presented with a specification of portion size in gram or millilitre and an additional explanation (e.g. "portion size is 200 ml, this equates approximately 1 glass").
After answering some questions on demographic variables, body weight and height, each subject received a short, standardised description of the label format of his or her experimental condition and its meaning and after that completed two tasks: 1. Pair-wise comparison of foods and 2. virtual grocery.
Task 1: Pair-wise comparison of foods
Participants were shown pictures (as described above) of 28 food pairs from the following food groups: drinks (3 pairs), fat/oils/sauces (4 pairs), meat/fish/sausages (6 pairs), dairy products (8 pairs), bread/cereals/grain products (3 pairs), fruits/vegetables (1 pair) and candies/snacks (3 pairs). The selection of the food pairs was made with the attempt to produce a representative sample of foods from the different food categories commonly eaten. Dieticians with experience in applied nutritional counselling were interviewed to find the appropriate food items. These food items were selected only if a healthy alternative was available and commonly eaten. Photographed foods were shown on cards with portion size information and food label corresponding to the experimental condition. Each food pair consisted of a healthier and less healthy variant. The healthier variant had less fat, saturated fat, sugar, sodium or energy than its counterpart. In case of bread for e.g. the healthier variant was 'whole grain bread' and 'whole grain toast' (see Additional file 1).
Additional file 1. Percentage of correct choices in the pair-wise comparison task 1. Food pairs used in the pair wise comparison task 1 (the less healthy food in brackets) and percentage of correct choices within each experimental condition (signpost format). The highest percentages are printed bold.
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Participants were informed that the presented food pairs were labelled with a signpost or, in case of "no label", with no nutrition label. It was explained, that the purpose of the study was to investigate whether food labels help to identify the "healthier variant, particularly with regard to a healthy body weight" of different foods. Then successively each pair of food cards was presented and participants were asked to identify the healthier food in each pair.
Task 2: Virtual grocery: Envisaged daily food consumption
For the virtual grocery task a shopping situation was simulated. 78 food pictures (including the 56 from task one) were placed in front of the participants, arranged in different food groups (identical to the categories in task one). In the same manner as for task 1 each food picture was labelled with the portion size and the signpost/or not of the experimental condition to which the participant was allocated.
The participants were asked to simulate a shopping situation, in which they select all foods and drinks, they would like to consume on the next day (e.g. for breakfast, lunch, dinner, snack). They were told that they could only select from the presented foods and were asked to specify how many portions they will buy for the envisaged consumption for the next day.
The presented foods were chosen in order to enable the participants to compose a day's consumption pattern that would comply with current dietary guidelines and recommendations [7]. The 78 foods could only represent a small variety of food items usually available in supermarkets. Therefore, the participants were asked to imagine being in a small "grocery around the corner" with a limited range of products. In addition they were told that the products' flavours shown on the photos in particular for yoghurt, jam or fruits could be substituted by other liked flavours.
In order to assess the possible impact of food labels on usual food choice the subjects were not explicitly prompted to make healthy food choices. However, since the virtual grocery was the second task after having identified the healthier food variants in task one, and the 56 food pictures from task one were used again in this task, there might have been an implicit inclination towards healthy food choices.
Subject recruitment and randomisation
A total of 30 interviewers investigated 14 subjects each. Each interviewer was asked to recruit a convenience sample of 7 female and 7 male subjects aged between 18 and 80 years. Subjects with training or work experience in the nutrition sector (e.g. dieticians, nutritionists, physicians, fellow dietetic students, etc.) were excluded.
Each of the 30 interviewers was assigned to investigate 2 of the 5 experimental conditions. Since there were 10 possible pair wise combinations of the 5 conditions (e.g. no label – simple tick, no label – traffic light ...), 3 interviewers were assigned to each of 10 pair wise combinations using a random number generator. Each interviewer received a list – again randomly generated – that detailed the sequence in which his or her 14 interview subjects were assigned to the experimental conditions. Thus, each of the 420 subjects was assigned to one experimental condition, i.e. one label format randomly. This procedure yielded 84 subjects within each of the five experimental groups.
Statistical analysis
Statistical analyses were done using SPSS Version 16 for Windows. Descriptive statistics are shown as mean ± standard deviation unless noted otherwise. From self-reported body weight and height Body Mass Index (BMI) was computed as BMI = kg/m2. For task 2 (virtual grocery) the total energy and nutrient intake as well as the energy density of the envisaged food consumption was computed using the nutrition information for the sample foods. Group differences in both tasks were examined using chi square tests for categorical variables and one way ANOVAs for continuous variables. To examine significant differences between means in more detail, post-hoc t-tests were computed after significant ANOVA results. Since these post-hoc test had exploratory character we abstained from adjusting significance levels for multiple testing.
In order to investigate whether sex, educational level and body weight status had an additional influence two-way ANOVAs were computed using experimental condition as the first factor and sex, educational level or weight group as the second factor. In the analysis of educational level 2 subjects were excluded who did not report an appropriate answer. For the analysis of weight status two groups were built: normal weight subjects with a BMI < 25 (including some underweight subjects) and overweight subjects with a BMI ≥ 25 (including some obese subjects). The significance level for all tests was set to p < 0.05.
In total, 420 participants took part in this study. 84 subjects participated in each of the 5 experimental groups. The sample characteristics are described in table 1. The experimental groups did not differ significantly with regard to sex distribution (CHI-square = 1.8; df = 4; p = 0.769), average age (F = 0.29; df = 4/415; p = 0.886) average BMI (F = 1.02; df = 4/415; p = 0.396) and educational level (CHI-square = 16.0; df = 12; p = 0.19). The BMI ranged from 17.1 to 43.3. N = 278 subjects (66.2% of the sample) had a BMI below 25, and n = 142 (33.8%) had a BMI of 25 or more.
Table 1. Socio-demographic characteristics and BMI of the study participants
Task one: Pair wise Comparison of foods
Additional file 1 shows the percentage of subjects within each experimental condition which correctly identified the healthier alternative in the pair wise comparison of foods. Significant differences between the percentages of correct healthy choices were found for 22 of the 28 food pairs. In 14 comparisons with significant differences the traffic light label yielded the highest percentage of correct choices. In addition, the traffic light label yielded the highest percentage of correct choices in 5 comparisons without significant differences. The highest percentage of correct choices was shared with GDA in two food pair comparisons and with coloured GDA in two other comparisons. In 2 comparisons the highest percentage of correct choices was associated with the GDA label, plus 2 comparisons where the highest percentage of correct choices was shared with the traffic light label. The coloured GDA label shared the highest percentage of correct choices in two pairs with the traffic light label. The simple "tick" had the highest percentage of correct choices in four comparisons (including one without significant differences); "no label" was only in one pair wise comparison associated with the highest percentage of correct choices.
The average number of correct choices for each subject differed significantly between the experimental conditions and hence the different signpost formats (F = 28.7; df = 4/415; p < 0.001) (see table 2). The traffic light label yielded the highest average of 24.8 correct choices between the 28 pairs. The "no label" condition was associated with the lowest average of correct choices (20.2 of 28 pairs). To examine these differences in more detail post-hoc t-tests between each pair of label formats were computed. The average number of correct choices did not differ significantly between the GDA and coloured GDA format. All other comparisons yielded significant differences in the number of correct choices between the different label conditions (p < 0.01).
Table 2. Mean number of correct healthier choices (± SD) in the pair wise comparison task (Task 1)
To explore possible influences of gender, educational status and weight status additional two-way ANOVAs were computed. The two-way ANOVA using label format and sex as independent factors yielded significant main effects for both label format (F = 30.0; df = 4/410; p < 0.001) and sex (F = 7.9; df = 1/410; p < 0.01). The interaction between the two factors was not statistically significant (F = 7.6; df = 4/410) indicating that the influence of gender did not differ between the experimental conditions. Inspection of the means (Table 2) shows that women had a slightly higher average number of correct choices. The two-way ANOVA using label format and educational level as independent factors yielded only one significant main effect for label format (F = 11.0; df = 4/403; p < 0.001). Neither the main effect of education (F 0 1.1; df = 2/403) nor the interaction (F = 0.9; df = 8/403) attained significance. The two-way ANOVA using label format and weight group as independent factors yielded significant main effects of label format (F = 24.2; df = 4/410; p < 0.001) and weight group (F = 8.1; df = 1/410; p < 0.01). The interaction between these factors was not significant (F = 0.2; df = 4/410) indicating that weight status did not affect the number of correct decision differentially between the experimental conditions. An inspection of the means (Table 2) showed that overweight subjects had a slightly lower number of correct decisions compared to normal weight subjects.
Task 2: Envisaged daily food consumption (Virtual grocery)
The envisaged daily consumption of energy and nutrients which was computed from the food choices in the virtual grocery task. The means and standard deviations are described in Additional file 2 for the 5 experimental groups. A comparison with the corresponding values from the German national nutrition survey II [33] is provided in Additional file 3. In all experimental groups the average daily intake for fat, saturated fat, sugar and sodium was above the recommendations for daily consumption (Additional file 2). One way ANOVAs were used to examine differences between the experimental conditions. Intakes of energy, nutrients in gram and nutrients as percentage of energy intake did not differ significantly between the examined label formats.
Additional file 2. Envisaged daily consumption of energy and nutrients (gram and energy percent) in the virtual grocery task (task 2). The data provided represent the mean ± standard deviation of the envisaged daily consumption of energy and nutrients in the virtual grocery task.
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Additional file 3. Total envisaged daily consumption compared with the results of the German National Nutrition Survey II (NVS II). The data provided represent the mean ± standard deviation and the median of the envisaged daily consumption of energy and nutrients from the total sample (all experimental conditions combined) in the virtual grocery task and a comparison with the mean and median of intakes in the German National Nutrition Survey II (NVS II) [33].
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To analyse possible interactions between subject characteristics and label format, additional two-way ANOVAs were computed using label format as one factor, and sex, educational level and weight status as the second factor. The analysis using sex as the second factor yielded significant main effects for sex for all outcome parameters except energy-percent of protein. Men had significantly higher envisaged consumptions of energy, grams fat, grams saturated fat, grams protein, grams sugar, grams carbohydrates, grams sodium, energy percent from fat, energy percent from saturated fat, lower energy percent from carbohydrates, and a higher energy density of chosen foods. Neither the main effect of food labels nor the interaction between sex and food labels attained significance, indicating that these sex differences were similarly present for each label format.
Using educational level as a second factor, the two-way ANOVA yielded a significant interaction between label format and education for sodium intake (in grams) (F = 2.2; df = 8/403; p < 0.05) and protein (in grams) (F = 2.4; df = 8/403; p < 0.05). All other effects did not reach statistical significance. Higher sodium intake was associated with higher education in the traffic light and coloured GDA condition, but with lower educational level in the simple tick condition (means are not presented in this paper). No systematic variation was found for the two other labels. For proteins, increasing educational level was associated with lower intake in the simple tick condition, with higher intake in the traffic light condition and with no systematic relationship in the other label conditions.
In the analysis using weight status as a second factor only the two-way ANOVA on energy percent from carbohydrates yielded significant main effects of experimental condition (F = 2.8; df = 4/410; p < 0.05) and BMI group (F = 5.0; df = 1/410; p < 0.05). An inspection of the means (not presented in detail in this paper) showed that normal weight subjects had higher energy percentages from carbohydrates than overweight subjects. The energy percent from carbohydrates was lowest in the CGDA-condition and highest in the "no label" condition (see Additional file 2).
Discussion and conclusion
Aim of the present paper was to investigate whether different formats of signpost food labels help consumers to differentiate between healthy foods, healthy particularly with respect to body weight, and less healthy foods, and whether they are likely to have an impact on consumers' food choices.
So far some research has been conducted on the subjective understanding of nutrition information. Studies show, that consumers think they do understand the nutrition information on food packages correctly which has been called subjective understanding [25]. However, less work has been done to assess the actual, objective understanding of such information. In our study we assessed the objective understanding of nutrition information given in different signpost food label formats by testing whether subjects were actually able to identify the healthier food variants.
Results from our study clearly indicate that signpost labels help to identify healthier foods better than un-labelled food. We also found differences in the efficacy of the different label formats to support the correct decision about healthier food variants. In our study, clearly, the multiple traffic light system showed the best performance. For most of the pair-wise comparisons the traffic light format showed the highest percentage of correct choices, and also the overall number of correct decisions was highest in this format. However, the differences between the different label formats were only moderate. Without any signpost label, the study participants correctly identified the healthier food in 20.2 of 28 pair-wise comparisons, while in the multiple traffic light label system correct choices were made in 24.8 of 28 cases. The simple "healthy choice" tick, the monochrome GDA label and the coloured GDA label resulted in an average number of correct decisions between no label and multiple traffic light label. Interestingly enough, adding traffic light colours to the monochrome GDA showed only a modest, statistically not significant increase in the number of correct choices. The results point partially to foods or food groups where food labels may be of particular value. In our dataset without food labels only a minority of subjects was able to identify milk chocolate as the healthier alternative in terms of fat, saturated fat and sugar. And even with food labels a large portion of subjects comes to a wrong decision regarding the "healthy variant particularly with regard to a healthy body weight". Presumably people use in their health evaluations knowledge from the media which portrayed dark chocolate as healthy due to its health protecting ingredients as e.g. flavonoids. Such information seems to overwrite other information even if people are prompted to consider body weight.
In addition we did not find that the various signpost formats affected the different subject groups differently. In general, women in comparison to men and normal weight subjects in comparison to overweight subjects had a higher number of correct decisions, but since this was the case for all experimental conditions it was independent from the label format. Interestingly enough, we also failed to find an influence of education status on the number of correct decisions.
These outcomes are consistent with research from the Food Standards Agency, London (FSA) where consumers could imagine using food label information, especially when the information is colour-coded, and in cases where there is a range of product alternatives in the same product category, the items may differ in their "colour range" [25,34]. A recent study, which is not fully published yet, revealed a good understanding of the nutrition labelling schemes used in the UK. Most consumers were able to rank food products correctly in terms of healthiness regardless of the labelling system [20,35]. This corresponds to the only modest difference in the number of correct decisions of healthier food choices among the different food label formats in our study.
If nutrition information given in the form of signpost food labels has an impact on the perceived healthiness of foods, it is an independent question whether the perceived healthiness is likely to ultimately influence food choice and food intake.
A recent pre-published study shows that only one in four shoppers actually looks for nutrition information on food packages in supermarkets [20]. It is obvious that most consumers read nutrition information when exposed to it accidentally rather than seeking for it deliberately [25]. In addition, label use is negatively linked to time pressure [25]. On average European consumers spend between 25 seconds (UK) and 47 seconds (Hungary) per product bought in a supermarket [35]. Consequently several situational, behavioural and attitudinal factors like income, time or household size have an effect on the use of on-pack nutrition information and therefore influence on the food choices [14]. Furthermore, nutrition labelling is only one of several information sources available to consumers. Media, advertising and promotion activities can also affect consumers' choices [10,36]. This may prompt nutritionists to consider the limitations of nutrition labels for health promotion [21].
Former research has shown that the self-reported use of food labels is associated with lower fat intake [37-39] and higher fruit and vegetable intake [37]. However, the causal nature of this association is not quite clear. Indeed, results from a study by Lin et al. [40] suggests that lower intake of fat, saturated fats and cholesterol will increase the probability of searching for information about these nutrients. In line with such considerations is the finding that prior nutritional knowledge predicts the use of food labels [41].
A recently published study found that subjects had the intention to change their future food choice when they were exposed to signpost labels of food products they usually eat and of food products that represented healthier variants of comparable food [26]. Subjects reported an intended increase of consumption frequency of less than one portion every two weeks of the healthier food variants. In addition they reported an intended decrease of consumption frequency of one portion per week of the usually eaten food for which they had been shown a healthier variant. There was no significant difference between different label formats.
In our study we asked our subjects to select foods they would like to eat during one day from a "virtual grocery". The resulting envisaged one day's food consumption was quite realistic, even though the total energy intake was slightly higher than the average energy intake in Germany, particularly in men [33]. In line with the results of Feunekes et al. [26] we could not find an influence of food label formats on any parameter of food consumption: Neither energy intake nor any of the examined nutrients or energy density of total envisaged food intake varied between the different experimental conditions. This pattern of results was maintained even if subject characteristics like gender, educational level or weight status were taken into account. For most parameters we found no statistical interaction of label format and subject characteristics indicating that the effect of label format was the same within each subject group. The only exceptions were sodium and protein intake in relation to educational level. However these variations were neither large nor systematic. These few significant interactions could be attributed to the multiple tests in this explanatory analysis.
Hence, results from the second task of our study show that even if a food's perceived healthiness is influenced by using signpost labels this is unlikely to have any major impact on the actual food choice.
This is in line with results from Grunert and Wills' review [25]: when buying intentions for products with or without signposts (health logos, traffic light, GDA-based systems) were measured, the use of labels would not prevent consumers from eating products which they like for their taste [25].
Despite the finding that food labels have no major impact on individual food choices, one effect of nutrition labelling – in particular with prominent symbols like traffic lights – could be the production of more healthy food products as manufacturers might wish to make their products more attractive with more favourable signposts [10]. This is endorsed by observations from Sainsbury's and Tesco which seem to indicate that, after introduction of their signposting system (the Wheel of Health, a colour-coded GDA system, for Sainsbury's and a not colour-coded GDA system for Tesco), sales of some healthier products went up whereas sales of comparable products with less favourable nutrient information went down [25]. Such changes would imply that signposting does change individual shopping behaviour. However, to our knowledge, the methods used and conclusions drawn from the Sainsbury's and Tesco findings have not been scientifically reported and can therefore be given only little credence.
Our study has some limitations which have to be discussed before drawing conclusions. First of all, our study sample was a convenience sample of adults recruited in the area of Hamburg (Germany). Thus our sample can not be considered as representative of the general population. This is particularly true, since we had a considerably higher number of subjects with high educational level than would be expected in a representative sample. We did not test or investigate nutrition knowledge of our subjects. Thus we can not exclude that a particular level of nutrition knowledge in our sample has contributed to our findings. In addition, owing to the fact that the interviewers recruited the study participants themselves, the potential for interviewer bias might be higher as the interviewers may have been more prone to recruit specific socio-demographic types, which could have influenced the results. However, given this limitation, analyses taking into account the different levels of education did not find any hints that educational level differentially affected the understanding of food labels, the perceived healthiness of foods resulting from the understanding of the food labels or the intended/envisaged consumption of food labelled in different formats. Nevertheless, increasing the sample size or including a substantially higher number of subjects with low educational status might increase the power to detect differences related to education which we missed with our convenience sample. In addition, our findings may not be valid for consumers in other countries, and we can not extrapolate from our findings in adults the possible impact food labels could have in children and adolescents.
A second limitation stems from the fact that we could only use a limited number of food items in our study. However, in investigating the understanding of food labels and the resulting perceived healthiness of foods we used 28 pairs of foods from different food groups which is considerably more than has been used in other studies [26,35]. In the second task of selecting food items for envisaged one-day consumption in a virtual grocery again we used only 78 foods, which is a very small number compared to the thousands of different products available in real supermarkets. Nevertheless, our subjects did not complain about this limitation and the resulting envisaged intakes were quite equivalent to average German consumption patterns with a slightly elevated energy intake in our study subjects, particularly in men. In addition to the limited number of foods, some bias might result from the fact that within the different food groups, different number of foods or food pairs were selected for the experimental procedure. The results of the pair-wise comparison task indicated that different labelling systems favoured different products. Thus the results may be biased by the over-representation of some product groups, e.g. we used 8 dairy product pairs in which the traffic light system most often produced the highest percentage of correct responses, but only three grain/cereal comparison in which the simple "tick" logo yielded the highest percentage of correct responses. Therefore a different composition of the number of foods within each food group may yield different results.
Of course, a third important limitation is that we examined only virtual, intended or envisaged food consumption and not real shopping or consumption behaviour. The selection of foods in this task for the envisaged consumption during one day, of course, is a rather artificial experimental situation. Thus, in real shopping situations a number of different factors and processes may influence shopping decisions and food choice. For example, promotion activities and discount offers may influence the shopping behaviour as well as shopping habits in a super-market that is familiar to the subject. In addition, in real life people eventually eat what they have bought, in this virtual task they were aware that their shopping choice was without real consequences. These differences may have biased our results. However, since we were interested in examining the influence of different food label formats on food choice there is little reason to believe that the labels would result in differences in real behaviour whereas they did not result in differences in our virtual, experimental situation. In addition, the experimental situation and the limited number of foods may contribute to the lack of differences in the virtual grocery task. The pair-wise comparison task showed that, overall there were only modest differences between the different label formats. Given these small differences it may be suspected that subjects would select a similar diet if they were asked to present a healthy food choice to the interviewer as might be implied by the experimental context. Thus, we can not exclude that a wider selection of foods might yield a better chance for the different labels format to produce differences in food choice.
A forth limitation lies in the criteria which we used for assigning the "tick" label. The "tick" label was only given, when all of the criteria to award the "green" colour for fat, saturated fat, sugar and sodium were fulfilled. This may represent a rather restrictive approach. Therefore results may be different if other approaches or criteria are used.
A fifth limitation is related to our conclusions regarding different body weight groups. We calculated BMI from self-reported weight and height which is known to be inaccurate and have restricted validity. Thus some of the subjects might have been misclassified as normal weight or overweight, and we can not exclude that results from weight related analyses would be slightly different if we had actually measured weight and height. However, all other inferences should not be influenced by this limitation.
Keeping in view of the limitations mentioned above, the results from our study would justify the following conclusions: (1) Signpost food labels may influence the perceived healthiness of food products by the consumer. (2) Different label formats differ in how effectively they help the consumer to identify the more healthy food when comparing different foods from the same food category. In our study, clearly the multiple traffic light format helped consumers most, to identify the healthier variant of foods. However, currently in real life, the German consumers are only exposed to the GDA food labels which are voluntarily printed on the products. Therefore, it is not clear whether the understanding of food labels will change when one or the other label format comes into wider use and becomes more familiar to consumers. In addition, for the sample foods of our study the decision which variant of a food was more or less healthy was unambiguous because the differences between the variants were only for one nutrient or for multiple nutrients in the same direction. It remains totally unclear how consumers would evaluate the healthiness of foods in a comparison where one food has for example a high sugar and low fat content whereas the other has a high fat, but low sugar content. (3) Despite the fact that food labels may influence the perceived healthiness of foods by the consumers, this is unlikely to have a major impact on food choice and consumption. Thus, there is little reason to assume that signpost food labels will be an effective instrument in the prevention of overweight and diet related diseases.
In our study, we were not able to address a number of issues and questions which should be addressed by future research. Children and adolescents are an important target group for the prevention of overweight and diet related diseases. Which type of food labels helps them best to differentiate between more or less healthy foods? Children and adolescents with migrant background have a particularly high prevalence of overweight and obesity in Germany [4]. Are there cultural differences in the understanding and use of food labels in groups with migrant and non-migrant background? Although we did not find differences in the understanding und use of food labels between different educational levels in our study, it may be useful to address socio-economic status as a primary variable in specifically designed studies. We also did not include motivational or attitudinal variables in our study. Future studies should examine whether subjects with different attitudes and/or motivations differ in their understanding of and profit from the use of different food labels. In addition, systematically examining, how other factors, particularly attitudinal and motivational variables that influence food choice, may be changed in order to achieve healthier food choices in different target population groups, may yield valuable information.
Competing interests
JW has been consulting Mars Deutschland GmbH with regard to snacking behaviour of children.
IB has no competing interests.
Authors' contributions
Both authors contributed similarly to the design of the study, analysis and interpretation of the results, and to the preparation, revision and final approval of the manuscript. In addition, IB has been primarily responsible for conducting of the study. All authors have read and approved the final manuscript.
Authors' information
IB graduated in Public Health (Diplom-Gesundheitswirtin). She works as a research fellow at the Public Health Research Group of the Hamburg University of Applied Sciences.
JW is Professor of Nutritional Psychology and Health Psychology, Head of Public Health Research Group and Head of the Department Health Sciences at the Hamburg University of Applied Sciences, and Secretary of the German Society for the Study of Obesity.
No external funding has been available for this study.
The authors like to thank the students of the Hamburg University of Applied Sciences, Public Health Nutrition Course of the summer semester 2008 who conducted the interviews in the present study.
The valuable help of Mrs. Sibylle Adam and Mrs. Tamara Tuchscherer in preparing study materials and literature search is gratefully appreciated.
We like to thank Amena Ahmad, Eva Grammatikaki, Peter Scarborough and Klaus G. Grunert for their valuable comments on a earlier version of the paper which helped us much to enhance the manuscript.
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Pre-publication history
The pre-publication history for this paper can be accessed here:


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List of Killer Instinct characters
|This article needs additional citations for verification. (June 2012)
The following is a list of characters in the Killer Instinct series of fighting games.
- 1 Roster
- 2 Introduced in Killer Instinct
- 3 Introduced in Killer Instinct 2
- 4 Introduced in Killer Instinct (2013)
- 5 References
|Black Orchid
|Chief Thunder
|Kim Wu
|Shadow Jago
|T.J. Combo
- Boss, secret playable character
- Guest character
Introduced in Killer Instinct[edit]
Black Orchid[edit]
Chief Thunder[edit]
- Voiced by: Ken Lobb
Chief Thunder, AKA Hinnamatoom, a Native American chief of Nez Perce origin, armed with twin tomahawks, enters the tournament to find out what happened to his missing brother Eagle in the previous year's tournament. In the series' third entry, he has since discovered his brother, Eagle, was killed in the first Killer Instinct tournament, though no body was found to confirm his demise or how it occurred. Grieving, Thunder dons his war paint and begins fighting opponents to try and determine what became of his brother, allying with the mysterious ARIA in the hopes of finding Eagle's remains and receiving closure. Upon learning that his brother was used in the construction of a Fulgore unit, however, he swears vengeance for the mutilation and begins searching for the Fulgore containing Eagle's body, later receiving assistance in his quest from Aganos.
In 2008, GamesRadar featured him on a list of top seven native American stereotypes in games as one of three examples of the "Warrior" stereotype.[1] In 2011, Dorkly ranked him the most stereotypical native American character in fighting-game history.[2] In the 2013 Killer Instinct, his fighting has been revised to be based more heavily around grappling than the other characters. His character design was also revamped to be more culturally sensitive towards Native Americans, with help from a Nez Perce tribesman.[3]
Ben Ferris is a convicted criminal who was promised early parole in exchange for participating in UltraTech's chemical-weapons research. As a result of an accident during testing, his body is composed entirely of flame. Now going by the code name Cinder, he is promised a return to his original form if he is able to defeat Glacius in the tournament. However, Cinder ultimately falls to Glacius and is killed.
Cinder returned as part of the second season of Killer Instinct for Xbox One, retconning his backstory. In this version, Ferris is a former military special operative turned career criminal, stealing information and secrets for corrupt corporations. When he receives an expensive contract to steal data regarding UltraTech's top-secret "Project Cinder", he infiltrates the organization, discovering the project to be of extraterrestrial origin. However, he is caught and exposed by ARIA and given an ultimatum: join her or be killed. Ferris agrees, and ends up being the first test subject for Project Cinder. His DNA is spliced with that of Glacius, causing his body to be consumed by plasma energy, though a mask and suit designed by Aria allows Cinder full control of his powers. Enjoying his new abilities, he now serves as ARIA's lieutenant, working alongside her to fulfill her plans. After eliminating Sadira on ARIA's orders, he is promoted to her second-in-command.
Cinder was rather notorious for his overpowered attacks in the original title. His infinite combo (present in early versions of the game) was deemed so problematic, developers had to manually install ROM updates to over 17,000 cabinets in order to remove the bug.[4] In the early development stages of Killer Instinct, Cinder went through multiple name changes, such as "Meltdown" and "Pyrotech".
Voiced by: Henry Sterchi & Isaac Marshall
The final boss, Eyedol is a two-headed, one-eyed ancient mystical warlord who was trapped in a dimensional prison in the distant past. UltraTech released him to be the final combatant in the tournament. In Killer Instinct 2 Eyedol was trapped in combat with Gargos, the final boss of that game. In Eyedol's ending, he is supposedly found by his mother (as a boy named "Billy") after going missing in a car crash as a child. However, Eyedol attacks her in a comical manner in a spoof of Blanka's original Street Fighter II ending.
Eyedol is the only character without an icon on the character-select screen. In early SNES versions of the game (released only to stores), he was selectable; however, in the arcade and SNES versions he is a secret character who can be played by selecting a specific character (Riptor in earlier arcade versions. and Cinder in later arcade and SNES versions) and pressing a combination of buttons before a round begins. He is the only character in the game with no special finishing moves (such as No Mercy moves, Ultra Combos or Humiliations); however, he compensates with a limited ability to heal.
Cheat Code Central included Eyedol in its 2012 list of top ten hidden characters in fighting games.[5]
- Voiced by: Kevin Bayliss (KI, KI2), Jean-Edouard Miclot (KI 2013)
Glacius is an alien who was captured by UltraTech and promised freedom if he wins the tournament. In the end, Glacius defeated Cinder and returned home. In Killer Instinct 2, a distant relative of Glacius from 2,000 years ago who shares his name heeds a distress call, coming to Earth to find his lost brethren and bring them home. The original Glacius returns to Earth in Killer Instinct for Xbox One, having been forced to leave some of his alien technology behind when he was last on the planet. Upon landing, his power core is stolen by Sadira, and he becomes determined to catch her and prevent his technology from falling into the wrong hands.
Glacius uses three No Mercy moves: one where he becomes a gel-like mass and absorbs the opponent, similar to the Blob (arcade only), one in which he uses his finger as a syringe to inject the enemy with a substance turning them to ice, and one in which he becomes a pool of boiling water in which the enemy drowns. He gets his nickname from his body's icy liquid composition and his ability to shape-shift. He is one of the few characters who retained his original name throughout the game's early development.
- Voiced by: Zachary Quarles (KI 2013)
Riptor is a genetically-engineered velociraptor-human hybrid created as a prototype by UltraTech; the tournament tests her abilities as a killing machine. However, she is ultimately defeated by T.J. Combo prior to KI2, but damages Combo's right eye during the confrontation. A new, enhanced Riptor appears as part of the second season of Killer Instinct for Xbox One. Created by UltraTech's military division under ARIA's orders, Riptor is the leader of a pack of cybernetic-enhanced raptors known as Project Stalker, meant to serve as an alternative to the Fulgore line and Cinder project, being able to operate in conditions ill-suited for either. The Stalkers are all augmented using leftover Fulgore technology and undergo a simulated upbringing through the mind of their creator, UltraTech scientist Erin Jupte, bred as assassins to eliminate perceived threats to Ultratech. Under ARIA's orders, Riptor and the Stalkers assault Maya's rebel force, trapping them while ARIA enacts her plan.
Riptor has three No Mercy moves: one in which she spits acid on the enemy, a second in which she stabs the foe with her tail, and a third in which she runs at the enemy, eating them.
Count Von Sabrewulf is afflicted with lycanthropy and promised a cure by UltraTech if he wins the tournament. In the sequel, Sabrewulf was captured by UltraTech after being severely injured during the first tournament, and has been driven mad by experimentation. With cybernetic arms, he desperately seeks a cure for his lycanthropy. In the third installment, Sabrewulf still seeks a cure, but has almost completely fallen to his feral side, compelling him to tear out his mechanical implants and regain his arms through Dark Arts. He also has become addicted to drugs which he used to ease his pain during the process of regaining his arms.
Sabrewulf, who was originally called "Cyberwulf", was inspired by the antagonist of Rare's 1984 game Sabre Wulf.[6] Sabrewulf fights in his inherited castle with biting and claw attacks and the ability to howl and use his flaming bats (although sometimes they do not flame).
- Voiced by: Chris Seavor (KI, KI2), David Robert Donatucci (KI 2013)
An animated skeleton, Spinal was reanimated by UltraTech but destroyed by Chief Thunder in the first tournament; however, Gargos had a Spinal of his own in the past. Spinal fights for vengeance and his freedom. Spinal reappears in Killer Instinct for Xbox One, resurrected by an artifact known as the Mask of the Ancients, and seeks to find it in hope of releasing himself from the curse of immortality, allowing him to finally rest in peace. However, ARIA takes control of him, forcing him to serve UltraTech.[7]
In the first Killer Instinct, Spinal is the third-last opponent in single-player mode; with a sword and shield, he can teleport and change himself into a grayscale version of his opponents during combos. Spinal has a quirk: to perform certain moves, he must gather energy—represented by tokens shaped like skulls under his life bar (SNES version) or skulls floating around him (arcade, Gold, and Xbox One versions)—by absorbing opponents' projectile-energy attacks (with his shield in absorbing position) or performing combo breakers. Despite requiring these tokens, his special moves are no stronger than normal special attacks. Spinal can store up to five skull tokens, overloading if he tries to absorb energy for the sixth time. On the sixth attempt he will not block the projectile, and it will cause normal damage and knockdown; he will then be left with one remaining skull.
T.J. Combo[edit]
- Voiced by: Patrick Seitz (KI 2013)
A former five-time heavyweight boxing champion, T.J. "Combo" Garrett was stripped of his title and expelled from the circuit when it was discovered that he had been cheating, having secretly had cybernetic enhancements implanted in his arms. UltraTech promises the disgraced boxer that he would be returned to his former glory if he wins the tournament. After his victory against Riptor in the first tournament, which also cost him his left eye, T.J. Combo was sent into the past and fights to return home.
In Killer Instinct for Xbox One, T.J. loses the Heavyweight Championship title after 20 years. Desperate to remain on top, he asks UltraTech to install illegal cybernetic augmentations in his arms in exchange for throwing a fight against Fulgore during a live exhibition for their customers. However, T.J. wins the fight, and UltraTech rips out the augments and exposes him as punishment, causing him to be banned from the ring. Seeking both vengeance and redemption, T.J. allies himself with Orchid, and they destroy a Stalker development facility, acquiring classified information on UltraTech's illegal experiments. The two break into the Pinnacle, with T.J. defeating the new Fulgore model protecting the facility, and barely escape as Orchid broadcasts their findings to the world, causing public perception of the company to plummet and UltraTech to go dark. Orchid allows T.J. to take credit for the exposure, and he is once again hailed by the public. He later appears as part of Maya's anti-UltraTech rebel force.
In 2012, Complex included him on a list of 25 "douchiest" video game characters.[8] The character was based on John Parrish (who also performed the motion capture for T.J. Combo in the original Killer Instinct), known for playing Jax in the early Mortal Kombat games.[9]
Introduced in Killer Instinct 2[edit]
Gargos is a demon lord who has returned to the physical world. He was Eyedol's rival, resembling a huge gargoyle who is powerful and can breathe fire. After being locked in combat with Eyedol for thousands of years, Eyedol's summoning and subsequent defeat gives Gargos the chance to begin his conquest anew. Jago's back story in the second installment reveals him to be the "Tiger Spirit" that led Jago to the first Killer Instinct tournament. Like Eyedol in the original game, Gargos may be accessed with a cheat code.
In Killer Instinct for Xbox One, Jago is attempting to purge the remains of Gargos's influence from within him. At one point, he is possessed by Gargos's herald, Omen, and turned into Shadow Jago to make him a potential host body for Gargos. However, Jago's will is too strong, and he forces Omen out. Eventually, Kan-Ra is tricked by ARIA into opening a portal to Gargos's dimension, and ARIA defeats Omen, prompting Gargos to emerge from the portal onto Earth. Gargos will appear as the primary antagonist of the game's third season.[10]
Kim Wu[edit]
Kim Wu is a 17-year-old East Asian female ninja[11] descended from the people who repelled Eyedol and Gargos. To protect her people, she tries to destroy Gargos. Kim Wu will appear as a playable character in the third season of Killer Instinct for Xbox One.[12]
Kim Wu's No Mercy moves are setting her opponents on fire with a blazing shuriken and jumping on them. Kim Wu is also an enemy to Spinal, a soul resurrected by UltraTech.
Maya Fallegeros is an Amazonian warrior who had banished Gargos prior to the events of Killer Instinct 2, for which she was heralded as a hero among her people. When Gargos reappears, Maya's tribe, feeling that she had failed them, casts her out. Maya's goal is to destroy Gargos and regain her former standing with her people. In Killer Instinct for Xbox One, Maya returns, now heavily redesigned with Incan-inspired armor and part of a secret society of monster-hunters known as the Night Guard, sealing away artifacts and monsters too powerful to destroy. When her people's hidden city is attacked by UltraTech, releasing Kan-Ra, Maya is left as the last surviving member of the Night Guard and takes up "Temperance" and "Vengeance", a pair of cursed daggers once used by Kan-Ra, to hunt down both him and the monsters that escaped. With Aganos' help, she eventually finds and defeats Kan-Ra, sending him through a portal to another dimension, but receives a vision of an impending invasion by the forces of Gargos and vows to reform the Night Guard and gain allies to fight in the coming war. She recruits Jago, Orchid, and T.J. Combo to her cause, but they are ambushed by UltraTech forces and trapped while ARIA completes her plan.
Maya's No Mercy (ultimate combo) moves are summoning an elephant to fall on her enemy and shrinking them with a ray from her headband. Her revealing jungle bikini earned her a place among the "Worst Dressed of 1996" according to Nintendo Power.[13] The magazine also nominated her elephant-drop ultimate combo move for its "That's Gotta Hurt" Award.[13]
Tusk is a barbarian who wants to fight all of the challengers for the right to destroy Gargos. In his ending, he and Maya are married following the defeat of Gargos. His ultimate-combo moves are summoning a meteor shower to pummel his opponent (with a large one crushing them) and summoning a dinosaur which eats the opponent. Tusk will appear as a playable character in the third season of Killer Instinct for Xbox One.[12]
Introduced in Killer Instinct (2013)[edit]
An ancient war golem, the last of its kind. Constructed as one of a thousand by powerful Babylonian artisans roughly 3500 years prior, the golem serves various masters as an obedient tool of war for a thousand years, replacing its damaged parts with whatever natural materials are available. Eventually, one King gives it the name Aganos (ἀγανός, "one of gentle disposition") and the order to learn and think for itself, hoping it would choose to overcome its original violent purpose. As thanks for being given free will, Aganos pledges loyalty to the King. However, after being betrayed by Kan-Ra and learning of his survival and growing dark power, the King orders Aganos to hunt down and kill Kan-Ra. Aganos accepts the task, and has since pursued Kan-Ra for centuries, though neither has yet been able to destroy the other. Eventually, both Aganos and Kan-Ra are captured by the Night Guard and imprisoned for over 500 years until the present day, when UltraTech's attack on the city releases them. Forced to resume his pursuit, Aganos allies with Maya to track down Kan-Ra and destroy him. Kan-Ra lays a trap for Aganos and steals most of his energy before escaping, leaving him too weak to fight back as Cinder installs Fulgore technology into him, allowing UltraTech to control Aganos's mind. Sent to attack Maya and her allies, he is ultimately freed from UltraTech by Thunder, who offers to help Aganos find Kan-Ra in exchange for help finding Eagle, to which Aganos agrees.
Aganos is the largest character in the Killer Instinct series. He has the ability to gather natural materials into his body, affecting his strength and maneuverability. These resources can be used as projectiles or to create destructible barriers behind or in front of himself, changing the boundaries of the stage.
An AI and the CEO of UltraTech. Beginning in the late 1940s, the Ultrafine Atomic Technologies Company, later rebranded as UltraTech, began attempting to simulate life and human frailty through a computational matrix. Called the Advanced Robotics Intelligence Architecture, or ARIA, the experiment was meant to find an end to famine, disease, poverty, and other forms of human suffering, with founder Ryat Adams hoping to cure the degenerative disease killing his wife. Using knowledge and technology gained from the Roswell UFO Incident, UltraTech continued to refine and enhance the ARIA core program over many years, drastically expanding its capabilities and understanding of the human condition. Following the passing of Adams, his will includes instructions for ARIA to continually run its programming to achieve its original purpose. In the present, ARIA leads UltraTech and carefully studies the rest of the cast during the first season. Believing humanity has grown weak and complacent as extraterrestrial and supernatural phenomena become more frequent, ARIA decides to force humanity to evolve by any means necessary. She enacts a plan to "prepare the way", building an army of Fulgores and Stalkers, stealing Glacius' DNA for use in Project Cinder, and tricking Kan-Ra into opening a rift to another dimension. ARIA's plan succeeds, and she summons Gargos to Earth, planning to use her armies to defeat the demon and become humanity's savior and ruler.
ARIA was first teased in a secret ending in Season One before becoming a playable character in Season Two. ARIA's AI is capable of uploading into one of three different combat drone bodies: Booster Drone, Blade Drone, and Bass Drone. The three share basic moves with the others, but each has its own set of unique special moves and properties, with ARIA able to switch between bodies during a fight and use all three at once during Instinct mode. Inactive drones can be called to assist ARIA, but this leaves them vulnerable to attack, limiting ARIA's abilities if any of them are destroyed; players can only defeat ARIA once all three drones are destroyed.
- Voiced by: Alpha Takahashi
A Japanese Onryō who lived during the Sengoku period of Japan. Over 500 years ago, a group of bandits leads a raid on a teenage girl's village. Her father, a former Samurai, is cut down attempting to stop them. Enraged, the girl takes up her father's naginata and continues his battle, slaughtering many of the raiders. Though she, too, is killed, her heroic sacrifice inspires the other villagers to fight even harder, successfully repelling the invaders. A shrine is erected in the girl's honor, where she is interred; her real name long forgotten, the villagers refer to her as Hisako (久子 lit. "Eternal Child"?), saying her spirit still protects the village. However, in the present, the village and her grave are desecrated by UltraTech due to ARIA's desire to study life after death, attempting to draw Hisako out. Hisako, having become an Onryō, reawakens and now seeks vengeance on UltraTech before she fades from the world once more. Defeating other supernatural beings to absorb their power and remain on the mortal plane, Hisako finds and defeats ARIA, allowing her spirit to rest once more.
Hisako uses a "Wrath meter" that gives her attacks the added effect of becoming counter-hits, even when her opponent does not attack, as well as a teleport, a low dash, and several command grabs.
- Voiced by: Edward Bosco
A 3500-year-old Babylonian Sorcerer. He was a royal Vizier who began researching immortality after developing a fascination with Aganos, the golem that served as the King's royal guard. His continued research into the dark arts leads him to attempt to steal the throne, planning to use a spell to seduce the Queen and have her murder the King. However, the spell wears off prematurely and the Queen kills herself out of guilt, exposing Kan-Ra's treachery. In retaliation, the King exiles him and orders his sorcerers to curse him with a withering rot that slowly disintegrates his flesh and organs. To prevent the rot from overtaking him, Kan-Ra places even more curses on himself to offset the rot's effects, seeking out magical artifacts and talisman to ease the pains brought on from the additional curses. He has since clashed many times with Aganos, under orders to destroy the sorcerer, but neither has ever managed to eliminate the other. Escaping to South America, he uses his powers to enslave the local population and force them to build a temple for him to conduct his studies. However, after being weakened in a battle with Aganos centuries earlier, he was unable to defend himself against the Night Guard, who burned him alive and locked away his ashes in the temple, which they claimed for themselves. Centuries later, an attack by UltraTech on the city accidentally releases him, and he escapes. Stealing Glacius's power core from Sadira, he uses it to create a Siphon, draining the energy from his foes to restore his own. Discovering Omen, he opens a portal in the temple to study him further, but is thrown in by Maya and discovers Gargos's army. Believing he can control them, Kan-Ra steals Aganos's energy and uses it to fully open the portal, but he inadvertently frees Gargos in the process, catching him by surprise and allowing ARIA to eliminate him.
Kan-Ra uses a fighting style based around magic and matter manipulation. He uses a number of ranged attacks, combined with ground and air-based trap techniques.
A winged demon calling himself the Herald of Gargos. Originally too weak to exist outside of a physical host, he briefly possesses Jago, transforming him into Shadow Jago, hoping to use him as a vessel to facilitate the return of Gargos. Ultimately, Jago's will proves too strong and Omen is forced out, but by battling foes while controlling Jago's body, he has gained enough strength to manifest on the mortal plane. In an attempt to lure Gargos out, Omen is later defeated by ARIA shortly after the portal to Gargos's dimension is opened.
Though he shares some basic moves with Jago, Omen has several unique abilities, including a mid-air dash, multiple types of projectiles with random effects, and a Shadow attack called Demonic Despair that converts all remaining health into white health if it connects. Omen is only available to players who purchase the Killer Instinct Season Two "Combo Breaker Pack" or "Ultra Edition".[14]
- Voiced by: Erika Harlacher
Sadira, the series' first female villain, is the leader of a clan of female assassins known as the Red Eyes of Rylai. She wears a maroon-colored outfit with spider symbols on it. She has pale skin, glossed purple lips, long black hair, and golden eyes. Her legs are visible through a gap in her clothing, and she wears high-heel sandals with tattered stockings. She makes extensive use of spider webs in her attacks, as well as forearm-mounted weapons consisting of metal claws and upright blades. ARIA recruits Sadira and her assassins to hunt down and kill the former competitors of the Killer Instinct tournament, and to "prepare the way" by stealing the power core from Glacius' ship and using it to open a rift to another dimension. The power core is stolen from her by Kan-Ra before she can use it, and after several failures, ARIA orders Cinder to eliminate her.
Sadira's gameplay is based around aerial juggle combos, a mechanic not seen in previous Killer Instinct titles. She was first revealed as part of the Thunder combo trailer, where CVG said she was "reminiscent of Mortal Kombat's Mileena in terms of design";[15] her name was revealed in a later stream by the developers.[16]
Shadow Jago[edit]
- ^ The Top 7… Native American stereotypes, GamesRadar US, 2008-11-24
- ^ Bridgman, Andrew. "The Dorklyst: The 7 Most Stereotypical Native American Characters in Fighting Game History". Dorkly Article. Retrieved 2012-07-30.
- ^ How Microsoft enlisted a Native American tribe to design a Killer Instinct character
- ^ http://www.eventhubs.com/news/2014/oct/13/cinders-infinite-forced-nintendo-manua lly-update-17000-arcade-cabinets-did-you-know-gaming-killer-instinct-ft-maximilian/
- ^ Angelo M. D'Argenio, Top Ten Hidden Characters In Fighting Games, Cheat Code Central, February 22, 2012
- ^ Ben (2011-06-22). "Top 5 Rare Characters Who Improved With Age – Rare – Blog". Rare.co.uk. Retrieved 2013-07-22.
- ^ "Killer Instinct: Orchid and Spinal Tease". IGN. 2013-10-31. Retrieved 2013-10-31.
- ^ "The 25 Douchiest Video Game Characters". Complex. 2012-04-18. Retrieved 2013-07-22.
- ^ "The On Blast Show! Episode 8". Youtube.com. 2011-01-08. Retrieved 2013-07-22.
- ^ http://www.ultra-combo.com/news-and-info-soon/
- ^ "NEXT Generation Issue #16 April 1996". Archive.org. 1996-04-16. Retrieved 2015-04-24.
- ^ a b http://www.ultra-combo.com/forums/index.php?topic=7993.0
- ^ a b Nintendo Power #96 (May 1997)
- ^ "The Textual Stream: 01/02/15 - The Herald approaches!". Ultra-combo.com. 2015-01-02. Retrieved 2015-04-24.
- ^ "News: Killer Instinct gets first original character". ComputerAndVideoGames.com. 2013-08-27. Retrieved 2013-10-15.
- ^ "KILLER INSTINCT: NEW Character Reveal (Spider Woman?!)". YouTube. 2013-08-23. Retrieved 2013-10-15.


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Propper Men's STL Long Sleeve Shirt - Easily access any concealed weapon you may have, while wearing the STL long sleeve shirt from PROPPER.
Propper Men's STL Long Sleeve Shirt - This shirt features dual chest pockets that have magnetic closures for quick and silent access. The stretch nylon and spandex fabric will help your body breathe and give you an excellent range of motion.
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