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  To generate the binary matrices, we employed a straightforward voting process. Three distinct evaluations were assigned to each document. In cases where a document received two or more identical classifications, the adopted value is set to 1; otherwise, it is marked as 0.Raw data can be checked into the repository in the [project repository](https://github.com/Silly-Machine/TuPy-Dataset)
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  The subsequent table provides a concise summary of the annotators' profiles and qualifications:
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- **Table 3 – Annotators’ profiles and qualifications.**
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  | Annotator | Gender | Education | Political | Color |
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  |--------------|--------|-----------------------------------------------|------------|--------|
 
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  To generate the binary matrices, we employed a straightforward voting process. Three distinct evaluations were assigned to each document. In cases where a document received two or more identical classifications, the adopted value is set to 1; otherwise, it is marked as 0.Raw data can be checked into the repository in the [project repository](https://github.com/Silly-Machine/TuPy-Dataset)
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  The subsequent table provides a concise summary of the annotators' profiles and qualifications:
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+ **Table 1 – Annotators’ profiles and qualifications.**
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  | Annotator | Gender | Education | Political | Color |
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  |--------------|--------|-----------------------------------------------|------------|--------|