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---
language:
- en
---

## PCL
Someone uses __Patronizing and Condescending Language (PCL)__ when their use of the language denotes a superior attitude towards someone else, or depicts them in a compassionate way, raising a feeling of pity among the audience. 

## pcl-roberta-base model for PCL detection
This model is trained on __Don't Patronize Me!__ , a dataset of paragraphs extracted from media articles about vulnerable communities, published in 20 English-speaking countries or areas. The paragraphs have been manually annotated to assess if they contain any type of PCL.
 
This is the PCL detection model built on roBERTa-base.

- Git Repo: [Don't Patronize Me! official repository](https://github.com/Perez-AlmendrosC/dontpatronizeme)
- Dataset: [Available upon request here] (https://docs.google.com/forms/d/e/1FAIpQLSe5KyzXgpnEOjS-Y6Gb8TTKiWxh4_qLuPL-NGiqKCyF41ALlg/viewform)

<b>Labels</b>: 
0 -> Negative;
1 -> Positive



To know more about our work on PCL detection, the PCL detection model and the dataset, please refer to: 

## Reference Papers: 


```
@inproceedings{perez2020don,
  title={Don’t Patronize Me! An Annotated Dataset with Patronizing and Condescending Language towards Vulnerable Communities},
  author={P{\'e}rez-Almendros, Carla and Anke, Luis Espinosa and Schockaert, Steven},
  booktitle={Proceedings of the 28th International Conference on Computational Linguistics},
  pages={5891--5902},
  year={2020}
}
```

```
@inproceedings{perez2022semeval,
  title={SemEval-2022 task 4: Patronizing and condescending language detection},
  author={P{\'e}rez-Almendros, Carla and Anke, Luis Espinosa and Schockaert, Steven},
  booktitle={Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)},
  pages={298--307},
  year={2022}
}
```

```
@inproceedings{perez2022identifying,
  title={Identifying condescending language: A tale of two distinct phenomena?},
  author={Perez-Almendros, Carla and Schockaert, Steven},
  booktitle={Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)},
  pages={130--141},
  year={2022}
}
```