{'fraction_non_alphanumeric': 0.03724604966139955, 'fraction_numerical': 0.012415349887133182, 'mean_word_length': 5.075342465753424, 'pattern_counts': {'":': 0, '<': 2, '<?xml version=': 0, '>': 2, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Understanding bias in proportion production.

The Stevens exponent (beta) can be obtained from proportion estimation judgments using the power model. In this article, the authors extend that model to proportion production, in which the relative magnitudes of 2 stimuli are adjusted to correspond to a numeric proportion (e.g., 1/4 or .25). The model predicts that when beta < 1, small proportions are underproduced, and large proportions are overproduced, but it predicts the reverse when beta > 1, which is the opposite of the predicted patterns for estimation. Eight participants estimated and produced magnitudes and proportions with spatial volume (beta < 1; Experiment 1) and color saturation (beta > 1; Experiment 2). The model's predictions were generally supported. An extension of the model using reference points can account for multicycle patterns shown by some participants.