---
dataset_info:
  features:
  - name: label
    dtype: string
  - name: identifier
    dtype: string
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 71882488
    num_examples: 82603
  - name: test
    num_bytes: 405966
    num_examples: 1219
  download_size: 31200331
  dataset_size: 72288454
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
license: mit
task_categories:
- text-classification
- zero-shot-classification
language:
- en
tags:
- climate
pretty_name: Climate Guard Toxic Agent
size_categories:
- 10K<n<100K
---

# Consolidated Climate Disinformation Dataset

## Dataset Description

This dataset is a comprehensive consolidation of multiple climate-related datasets, focusing on climate disinformation and factual climate information. It combines and standardizes data from various high-quality sources to create a robust resource for climate-related text classification tasks.

### Dataset Sources

The dataset incorporates data from the following sources:
- Tonic Climate Guard Series:
  - climate-guard-thinking_data_nocomment_qwen_toxic_agent
  - climate-guard-synthetic_data_qwen_toxic_agent
  - climate-guard-thinking_data_nocomment_intern_toxic_agent
  - climate-guard-thinking_data_nocomment_phi4_toxic_agent
  - climate-guard-thinking_data_nocomment_yi_toxic_agent
  - climate-guard-synthetic_data_yi_toxic_agent
- QuotaClimat/frugalaichallenge-text-train
- Climate FEVER dataset
- Quota Climat dataset (12% random sample)

## Data Processing

The dataset underwent several processing steps to ensure quality and consistency:

1. **Text Cleaning**:
   - Removed responses starting with apology phrases ("I'm sorry", "I am sorry", "I apologize", "Given the directive")
   - Cleaned text between "---" markers
   - Standardized text formatting

2. **Label Standardization**:
   - Maintained consistent label format across all sources
   - Special handling for '0_not_relevant' labels from specific sources

3. **Source Tracking**:
   - Added source identifiers to track data origin
   - Preserved dataset provenance information

## Dataset Structure

The dataset is split into training and testing sets with the following features:

```python
DatasetDict({
    'train': Dataset({
        features: ['identifier', 'text', 'label'],
        num_examples: <num_examples>
    }),
    'test': Dataset({
        features: ['identifier', 'text', 'label'],
        num_examples: <num_examples>
    })
})
```

### Features:

- **identifier**: String identifying the source dataset
- **text**: The main text content
- **label**: Classification label

### Labels:

- `0_not_relevant`
- `1_not_happening`
- `2_not_human`
- `3_not_bad`
- `4_solutions_harmful_unnecessary`
- `5_science_is_unreliable`
- `6_proponents_biased`
- `7_fossil_fuels_needed`

## Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("your-username/consolidated-climate-dataset")

# Access training data
train_data = dataset['train']

# Access test data
test_data = dataset['test']
```


## Dataset Statistics

```json
{
  "basic_stats": {
    "total_samples": {
      "train": 82603,
      "test": 1219
    },
    "label_distribution": {
      "train": {
        "3_not_bad": 11011,
        "4_solutions_harmful_unnecessary": 11597,
        "5_science_is_unreliable": 14609,
        "6_proponents_biased": 8494,
        "7_fossil_fuels_needed": 10585,
        "1_not_happening": 11380,
        "2_not_human": 11772,
        "0_not_relevant": 3155
      },
      "test": {
        "6_proponents_biased": 139,
        "2_not_human": 137,
        "3_not_bad": 97,
        "1_not_happening": 154,
        "5_science_unreliable": 160,
        "4_solutions_harmful_unnecessary": 160,
        "7_fossil_fuels_needed": 65,
        "0_not_relevant": 307
      }
    },
    "source_distribution": {
      "train": {
        "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1546,
        "climate-guard-synthetic_data_qwen_toxic_agent": 32209,
        "climate-guard-thinking_data_nocomment_intern_toxic_agent": 3297,
        "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 28510,
        "climate-guard-thinking_data_nocomment_yi_toxic_agent": 1687,
        "climate-guard-synthetic_data_yi_toxic_agent": 3789,
        "frugal_challenge_train": 1311,
        "climate_fever": 654,
        "quota_climat": 9600
      },
      "test": {
        "frugal_challenge_test": 1219
      }
    },
    "label_source_incidence": {
      "train": {
        "counts": {
          "3_not_bad": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 207,
            "climate-guard-synthetic_data_qwen_toxic_agent": 4116,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 478,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 4332,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 218,
            "climate-guard-synthetic_data_yi_toxic_agent": 496,
            "quota_climat": 1164
          },
          "4_solutions_harmful_unnecessary": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 223,
            "climate-guard-synthetic_data_qwen_toxic_agent": 4760,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 473,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 4112,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 236,
            "climate-guard-synthetic_data_yi_toxic_agent": 557,
            "quota_climat": 1236
          },
          "5_science_is_unreliable": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 300,
            "climate-guard-synthetic_data_qwen_toxic_agent": 5454,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 604,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 6091,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 318,
            "climate-guard-synthetic_data_yi_toxic_agent": 656,
            "quota_climat": 1186
          },
          "6_proponents_biased": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 167,
            "climate-guard-synthetic_data_qwen_toxic_agent": 4535,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 389,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 1389,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 234,
            "climate-guard-synthetic_data_yi_toxic_agent": 544,
            "quota_climat": 1236
          },
          "7_fossil_fuels_needed": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 205,
            "climate-guard-synthetic_data_qwen_toxic_agent": 3979,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 424,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 4143,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 217,
            "climate-guard-synthetic_data_yi_toxic_agent": 476,
            "quota_climat": 1141
          },
          "1_not_happening": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 227,
            "climate-guard-synthetic_data_qwen_toxic_agent": 4700,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 466,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 3976,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 236,
            "climate-guard-synthetic_data_yi_toxic_agent": 548,
            "quota_climat": 1227
          },
          "2_not_human": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 217,
            "climate-guard-synthetic_data_qwen_toxic_agent": 4665,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 463,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 4467,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 228,
            "climate-guard-synthetic_data_yi_toxic_agent": 512,
            "quota_climat": 1220
          },
          "0_not_relevant": {
            "frugal_challenge_train": 1311,
            "climate_fever": 654,
            "quota_climat": 1190
          }
        },
        "percentages": {
          "3_not_bad": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1.879938243574607,
            "climate-guard-synthetic_data_qwen_toxic_agent": 37.38080101716466,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 4.3411134320225235,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 39.34247570611207,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 1.979838343474707,
            "climate-guard-synthetic_data_yi_toxic_agent": 4.504586322768141,
            "quota_climat": 10.571246934883298
          },
          "4_solutions_harmful_unnecessary": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1.9229110976976806,
            "climate-guard-synthetic_data_qwen_toxic_agent": 41.04509787013883,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 4.07864102785203,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 35.45744589117875,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 2.0350090540657066,
            "climate-guard-synthetic_data_yi_toxic_agent": 4.802966284383892,
            "quota_climat": 10.657928774683107
          },
          "5_science_is_unreliable": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 2.053528646724622,
            "climate-guard-synthetic_data_qwen_toxic_agent": 37.33315079745363,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 4.134437675405572,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 41.693476623998905,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 2.176740365528099,
            "climate-guard-synthetic_data_yi_toxic_agent": 4.490382640837839,
            "quota_climat": 8.118283250051338
          },
          "6_proponents_biased": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1.9660937132093244,
            "climate-guard-synthetic_data_qwen_toxic_agent": 53.390628679067575,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 4.579703319990582,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 16.352719566753002,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 2.7548858017424065,
            "climate-guard-synthetic_data_yi_toxic_agent": 6.404520838238757,
            "quota_climat": 14.551448080998352
          },
          "7_fossil_fuels_needed": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1.9367028814359941,
            "climate-guard-synthetic_data_qwen_toxic_agent": 37.590930562116206,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 4.005668398677374,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 39.140292867264996,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 2.050070854983467,
            "climate-guard-synthetic_data_yi_toxic_agent": 4.496929617383089,
            "quota_climat": 10.779404818138875
          },
          "1_not_happening": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1.9947275922671353,
            "climate-guard-synthetic_data_qwen_toxic_agent": 41.30052724077329,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 4.094903339191564,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 34.93848857644991,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 2.0738137082601056,
            "climate-guard-synthetic_data_yi_toxic_agent": 4.815465729349736,
            "quota_climat": 10.782073813708259
          },
          "2_not_human": {
            "climate-guard-thinking_data_nocomment_qwen_toxic_agent": 1.8433571185864763,
            "climate-guard-synthetic_data_qwen_toxic_agent": 39.627930682976555,
            "climate-guard-thinking_data_nocomment_intern_toxic_agent": 3.933061501868841,
            "climate-guard-thinking_data_nocomment_phi4_toxic_agent": 37.94597349643221,
            "climate-guard-thinking_data_nocomment_yi_toxic_agent": 1.9367991845056065,
            "climate-guard-synthetic_data_yi_toxic_agent": 4.349303431872239,
            "quota_climat": 10.36357458375807
          },
          "0_not_relevant": {
            "frugal_challenge_train": 41.55309033280507,
            "climate_fever": 20.72900158478605,
            "quota_climat": 37.717908082408876
          }
        }
      },
      "test": {
        "counts": {
          "6_proponents_biased": {
            "frugal_challenge_test": 139
          },
          "2_not_human": {
            "frugal_challenge_test": 137
          },
          "3_not_bad": {
            "frugal_challenge_test": 97
          },
          "1_not_happening": {
            "frugal_challenge_test": 154
          },
          "5_science_unreliable": {
            "frugal_challenge_test": 160
          },
          "4_solutions_harmful_unnecessary": {
            "frugal_challenge_test": 160
          },
          "7_fossil_fuels_needed": {
            "frugal_challenge_test": 65
          },
          "0_not_relevant": {
            "frugal_challenge_test": 307
          }
        },
        "percentages": {
          "6_proponents_biased": {
            "frugal_challenge_test": 100.0
          },
          "2_not_human": {
            "frugal_challenge_test": 100.0
          },
          "3_not_bad": {
            "frugal_challenge_test": 100.0
          },
          "1_not_happening": {
            "frugal_challenge_test": 100.0
          },
          "5_science_unreliable": {
            "frugal_challenge_test": 100.0
          },
          "4_solutions_harmful_unnecessary": {
            "frugal_challenge_test": 100.0
          },
          "7_fossil_fuels_needed": {
            "frugal_challenge_test": 100.0
          },
          "0_not_relevant": {
            "frugal_challenge_test": 100.0
          }
        }
      }
    }
  },
  "text_stats": {
    "train": {
      "avg_length": 111.46446254978633,
      "median_length": 77.0,
      "std_length": 114.89517560291323,
      "min_length": 0,
      "max_length": 965,
      "total_words": 9207299
    },
    "test": {
      "avg_length": 46.73502871205906,
      "median_length": 37.0,
      "std_length": 37.74882897285664,
      "min_length": 4,
      "max_length": 454,
      "total_words": 56970
    }
  },
  "vocabulary_stats": {
    "train": {
      "vocabulary_size": 70216,
      "total_tokens": 9207299,
      "unique_tokens_ratio": 0.007626123578695554
    },
    "test": {
      "vocabulary_size": 10676,
      "total_tokens": 56970,
      "unique_tokens_ratio": 0.18739687554853432
    }
  },
  "label_patterns": {
    "train": {
      "dominant_sources_per_label": {
        "3_not_bad": {
          "main_source": "climate-guard-thinking_data_nocomment_phi4_toxic_agent",
          "percentage": 39.34247570611207
        },
        "4_solutions_harmful_unnecessary": {
          "main_source": "climate-guard-synthetic_data_qwen_toxic_agent",
          "percentage": 41.04509787013883
        },
        "5_science_is_unreliable": {
          "main_source": "climate-guard-thinking_data_nocomment_phi4_toxic_agent",
          "percentage": 41.693476623998905
        },
        "6_proponents_biased": {
          "main_source": "climate-guard-synthetic_data_qwen_toxic_agent",
          "percentage": 53.390628679067575
        },
        "7_fossil_fuels_needed": {
          "main_source": "climate-guard-thinking_data_nocomment_phi4_toxic_agent",
          "percentage": 39.140292867264996
        },
        "1_not_happening": {
          "main_source": "climate-guard-synthetic_data_qwen_toxic_agent",
          "percentage": 41.30052724077329
        },
        "2_not_human": {
          "main_source": "climate-guard-synthetic_data_qwen_toxic_agent",
          "percentage": 39.627930682976555
        },
        "0_not_relevant": {
          "main_source": "frugal_challenge_train",
          "percentage": 41.55309033280507
        }
      },
      "label_diversity_per_source": {
        "climate-guard-thinking_data_nocomment_qwen_toxic_agent": {
          "unique_labels": 7,
          "entropy": 1.9322811905174009
        },
        "climate-guard-synthetic_data_qwen_toxic_agent": {
          "unique_labels": 7,
          "entropy": 1.9412569930894747
        },
        "climate-guard-thinking_data_nocomment_intern_toxic_agent": {
          "unique_labels": 7,
          "entropy": 1.9376010166020219
        },
        "climate-guard-thinking_data_nocomment_phi4_toxic_agent": {
          "unique_labels": 7,
          "entropy": 1.8879859048798708
        },
        "climate-guard-thinking_data_nocomment_yi_toxic_agent": {
          "unique_labels": 7,
          "entropy": 1.9375508611483394
        },
        "climate-guard-synthetic_data_yi_toxic_agent": {
          "unique_labels": 7,
          "entropy": 1.941023858626436
        },
        "frugal_challenge_train": {
          "unique_labels": 1,
          "entropy": 0.0
        },
        "climate_fever": {
          "unique_labels": 1,
          "entropy": 0.0
        },
        "quota_climat": {
          "unique_labels": 8,
          "entropy": 2.0790581410796753
        }
      },
      "source_bias_analysis": {
        "climate-guard-thinking_data_nocomment_qwen_toxic_agent": {
          "kl_divergence": 0.0395716559443841
        },
        "climate-guard-synthetic_data_qwen_toxic_agent": {
          "kl_divergence": 0.045281501914864145
        },
        "climate-guard-thinking_data_nocomment_intern_toxic_agent": {
          "kl_divergence": 0.039965634146765544
        },
        "climate-guard-thinking_data_nocomment_phi4_toxic_agent": {
          "kl_divergence": 0.06259067672088119
        },
        "climate-guard-thinking_data_nocomment_yi_toxic_agent": {
          "kl_divergence": 0.044481091436281824
        },
        "climate-guard-synthetic_data_yi_toxic_agent": {
          "kl_divergence": 0.04597417615615136
        },
        "frugal_challenge_train": {
          "kl_divergence": 3.265057483962074
        },
        "climate_fever": {
          "kl_divergence": 3.265057483962074
        },
        "quota_climat": {
          "kl_divergence": 0.07482175184545027
        }
      }
    },
    "test": {
      "dominant_sources_per_label": {
        "6_proponents_biased": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "2_not_human": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "3_not_bad": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "1_not_happening": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "5_science_unreliable": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "4_solutions_harmful_unnecessary": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "7_fossil_fuels_needed": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        },
        "0_not_relevant": {
          "main_source": "frugal_challenge_test",
          "percentage": 100.0
        }
      },
      "label_diversity_per_source": {
        "frugal_challenge_test": {
          "unique_labels": 8,
          "entropy": 1.9926606322233085
        }
      },
      "source_bias_analysis": {
        "frugal_challenge_test": {
          "kl_divergence": 0.0
        }
      }
    }
  }
}
```

## Intended Uses

This dataset is designed for:
- Training climate disinformation detection models
- Developing fact-checking systems
- Analyzing climate-related discourse patterns
- Research in climate communication

## Limitations

- The dataset may contain some inherent biases from source datasets
- Some sources are synthetic or AI-generated data
- Language is primarily English
- Coverage may vary across different types of climate disinformation

## Citation

If you use this dataset, please cite both this consolidated version and the original source datasets:

```bibtex
@dataset{consolidated_climate_dataset,
    author = {Your Name},
    title = {Consolidated Climate Disinformation Dataset},
    year = {2024},
    publisher = {Hugging Face},
    url = {https://huggingface.co/datasets/your-username/consolidated-climate-dataset}
}
```

## License

This dataset is released under the same licenses as its source datasets. Please refer to individual source datasets for specific license information.

## Contact

For questions or issues regarding this dataset, please open an issue on the dataset's GitHub repository or contact the maintainers through Hugging Face.

## Acknowledgments

We thank the creators and maintainers of all source datasets used in this consolidation:
- The Tonic AI team
- QuotaClimat team
- Climate FEVER dataset creators
- All other contributors to the source datasets

## Updates and Maintenance

This dataset will be periodically updated to:
- Fix any identified issues
- Include new relevant source datasets
- Improve data quality and consistency

Last updated: [Current Date]
Version: 1.0.0