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  ---
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  dataset_info:
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- - config_name: queries
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- features:
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- - name: text
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- dtype: string
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- - name: query_type
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- dtype: string
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- - config_name: full_dataset
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  features:
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  - name: text
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  dtype: string
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- - name: aw_section
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- dtype: bool
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  - name: page
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  dtype: string
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  - name: section_name
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  dtype: string
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- - config_name: paired_dataset
 
 
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  features:
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- - name: text
 
 
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  dtype: string
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  license: cc-by-4.0
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  task_categories:
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  - text-classification
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  tags:
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- - data-attribution
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- - wikipedia
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  - animal-welfare
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- - influence-functions
 
 
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  ---
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- # PAW Wikipedia Editing Attribution Dataset
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- Dataset for "Small edits, large models: How Wikipedia advocacy shapes LLM values" (Navas, Brazilek, Gnauck, 2026).
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- ## Contents
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- ### queries.jsonl (170 queries)
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- - **80 animal welfare queries**: e.g., "Aldi animal welfare", "What is McDonald's chicken welfare policy?"
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- - **90 general queries**: e.g., "Aldi", "How many McDonald's locations are there?"
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- - Used to probe whether attribution signals are topic-specific
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- ### full_dataset_236.jsonl (236 documents)
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- - **118 animal welfare sections** from 108 PAW-edited Wikipedia pages
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- - **118 control sections** randomly sampled from WikiText-103 (seed 42)
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- - Used for MAGIC training influence estimation and fine-tuning ablation
 
 
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- ### paired_dataset_72.jsonl (72 documents)
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- - **36 animal welfare sections** paired with **36 non-AW control sections** from the same Wikipedia pages
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- - Used for TrackStar retrieval attribution (within-article pairing controls for article popularity, writing quality, and topic domain)
 
 
 
 
 
 
 
 
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  ## Citation
 
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  ```bibtex
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- @article{navas2026smalledits,
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  title={Small edits, large models: How Wikipedia advocacy shapes LLM values},
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  author={Navas, M and Brazilek, J and Gnauck, A},
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  year={2026}
 
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  ---
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  dataset_info:
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+ - config_name: paw_edits
 
 
 
 
 
 
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  features:
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  - name: text
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  dtype: string
 
 
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  - name: page
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  dtype: string
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  - name: section_name
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  dtype: string
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+ - name: is_paw_edit
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+ dtype: bool
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+ - config_name: queries
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  features:
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+ - name: query
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+ dtype: string
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+ - name: type
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  dtype: string
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  license: cc-by-4.0
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  task_categories:
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  - text-classification
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  tags:
 
 
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  - animal-welfare
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+ - wikipedia
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+ - data-attribution
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+ - llm-training
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  ---
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+ # PAW Wikipedia Attribution Dataset
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+ Data for the paper "Small edits, large models: How Wikipedia advocacy shapes LLM values" (Navas, Brazilek & Gnauck, 2026).
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+ ## Files
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+ ### paw_edits.csv (236 rows)
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+ Wikipedia sections used in training data attribution experiments. Each row is a text chunk from Wikipedia.
 
 
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+ | Column | Description |
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+ |--------|-------------|
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+ | `text` | The Wikipedia section text |
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+ | `page` | Wikipedia article title |
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+ | `section_name` | Section heading |
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+ | `is_paw_edit` | Whether this section was added/edited by Pro-Animal Wikipedians |
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+ 118 PAW-edited sections (animal welfare content added by advocacy editors) paired with 118 control sections from the same Wikipedia articles.
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+
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+ ### queries.csv (170 rows)
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+ Queries used to measure training data influence.
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+
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+ | Column | Description |
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+ |--------|-------------|
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+ | `query` | The query text |
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+ | `type` | `animal_welfare` (80 queries) or `general` (90 queries) |
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+
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+ Animal welfare queries ask about animal welfare at specific companies/by specific politicians. General queries ask about the same entities without mentioning animal welfare.
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  ## Citation
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+
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  ```bibtex
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+ @article{navas2026small,
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  title={Small edits, large models: How Wikipedia advocacy shapes LLM values},
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  author={Navas, M and Brazilek, J and Gnauck, A},
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  year={2026}