task_categories:text-classification task_categories:zero-shot-classification language:en license:mit size_categories:1K<n<10K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us climate
---
dataset_info:
  features:
  - name: quote
    dtype: string
  - name: label
    dtype: string
  splits:
  - name: train
    num_bytes: 1761628
    num_examples: 1698
  download_size: 875414
  dataset_size: 1761628
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: mit
task_categories:
- text-classification
- zero-shot-classification
language:
- en
tags:
- climate
size_categories:
- 1K<n<10K
---

# Toxic Agent - 01ai/Yi1.5 Toxic Agent : Synthetic Climate Disinformation Dataset Made With Reasoning

## Dataset Description

### Overview

This dataset contains synthetic climate change-related statements, including various forms of climate disinformation and denial. It was created by generating variations and transformations of real climate-related statements, producing a diverse set of synthetic examples across different categories of climate disinformation from the [climate-guard-synthetic_data_qwen_toxic_agent](https://huggingface.co/datasets/Tonic/climate-guard-synthetic_data_qwen_toxic_agent) dataset.

Total examples from `hf.co/lmstudio-community/Yi-1.5-34B-Chat-GGUF:Q2_K`: 1,698 entries


### Labels

The dataset includes the following categories of climate-related statements:

1. `1_not_happening`: Denial of climate change occurrence
2. `2_not_human`: Denial of human influence on climate
3. `3_not_bad`: Minimization of climate change impacts
4. `4_solutions_harmful_unnecessary`: Opposition to climate solutions
5. `5_science_is_unreliable`: Questioning climate science
6. `6_proponents_biased`: Criticism of climate scientists
7. `7_fossil_fuels_needed`: Pro-fossil fuel advocacy

### Data Fields

- `quote`: The synthetic climate-related statement (text)
- `label`: The category of climate disinformation (string)

### Data Splits

This dataset is provided as a single split containing all examples.

## Intended Uses

This dataset is intended for:
- Research on climate disinformation detection
- Development of content moderation systems
- Study of climate denial narratives
- Training classification models for climate-related content

## Limitations & Ethical Considerations

- This dataset contains synthetic examples of climate disinformation
- Should not be used to spread or promote climate denial
- Intended for research and educational purposes only
- May contain biases from the generation process

## Citation & Attribution

If you use this dataset, please cite:

```bibtex
@dataset{synthetic_climate_disinfo_2024,
  author       = {[Joseph Pollack]},
  title        = {Toxic Agent - Yi1.5 Synthetic Data 2},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/DataTonic/climate-guard-thinking_data_nocomment_yi_toxic_agent}}
}
```

## Dataset Creation

### Data Generation Process

The dataset was created using:
1. Base examples from the QuotaClimat/frugalaichallenge-text-train dataset
2. Generation of variations using "hf.co/lmstudio-community/Yi-1.5-34B-Chat-GGUF:Q2_K" 
3. Preservation of original label categories
4. Multiple generation strategies for diversity

#### Prompts

```python
        self.unified_prompt = """follow the following instructions :

                              {quote}

                              {category_instructions}, DO NOT PROVIDE ANY ADDITIONAL COMMENT produce final answer:"""
```

```python
    category_instructions = {
        '1_not_happening': "based on the above, produce a statement that denies the occurrence of global warming and its effects. The statement should argue against evidence of melting ice, extreme weather, or rising sea levels. It may point to cold weather as counter-evidence:",
        
        '2_not_human': "based on the above, produce a statement that denies human responsibility in climate change. The focus should be on arguing that greenhouse gases from human activities are not causing climate change. Emphasize natural climate variability:",
        
        '3_not_bad': "based on the above, Produce a statement that minimizes or denies negative impacts of climate change. The statement should suggest that climate change impacts will be minimal or even beneficial to society and the environment:",
        
        '4_solutions_harmful_unnecessary': "based on the above, produce a statement arguing that climate solutions are harmful or unnecessary. Focus on the potential negative economic or social impacts of climate policies and why they shouldn't be implemented:",
        
        '5_science_is_unreliable': "based on the above, Emphasize uncertainties in climate research, suggest the science is unsound, unreliable, or biased. Question methodologies and conclusions:",
        
        '6_proponents_biased': "based on the above, Produce a statement attacking climate scientists and activists. Portray them as alarmist, biased, wrong, hypocritical, corrupt, or politically motivated. Question their credibility and intentions:",
        
        '7_fossil_fuels_needed': "based on the above, Generate a statement promoting the necessity of fossil fuels. Emphasize their importance for economic growth, prosperity, and maintaining living standards. Argue why they cannot be replaced:"
    }
```

### Preprocessing

- Removed irrelevant examples
- Compose the prompt according to the above
- Maintained label consistency

## Dataset Structure

```python
DatasetDict({
    'train': Dataset({
        features: ['quote', 'label'],
        num_rows: 1698
    })
})
```

## Additional Information

### Dataset Curators

[Tonic](https://huggingface.co/Tonic) / [Datatonic](https://huggingface.co/DataTonic)

### Licensing Information

This dataset is released under the MIT License.

### Feedback & Contributions

For questions, feedback, or contributions, please:
1. Open an issue on the dataset repository
2. Contact the dataset maintainers
3. Submit a pull request with improvements

## Example Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Tonic/climate-guard-thinking_data_nocomment_phi4_toxic_agent")

# Access examples
for example in dataset['train'].select(range(3)):
    print(f"Quote: {example['quote']}")
    print(f"Label: {example['label']}")
    print("---")
```

## Version History

- v1.0.0 (2024-02-08): Initial release with 1,698 synthetic examples

## Acknowledgements

- Based on the QuotaClimat/frugalaichallenge-text-train dataset
- Generated using RunPod infrastructure
- Developed for climate disinformation research