Is Attention to Ignorance Growing? A Data-Driven Look at Developments in Ignorance Studies in the Twenty-First Century

This repository contains the primary dataset, Python extraction scripts, diagnostic tools, and supplementary appendix supporting the research paper "Is Attention to Ignorance Growing? A Data-Driven Look at Developments in Ignorance Studies in the Twenty-First Century". The dataset includes OpenAlex API bibliometric time-series data (2000–2025) normalized with the `has_abstract:true` filter, exact title/abstract substring verification records, diagnostic API scripts for the 2025 OpenAlex denominator anomaly, and control series tracking data for "misinformation studies" and "disinformation studies". Repository Contents (contained in Supplementary_Materials.zip):- Supplementary_Code_Appendix_v3.pdf: Methodological PDF appendix containing full annotated Python source code and reproduction instructions.- yearly_counts_v7.csv: Primary bibliometric time-series for agnotology and ignorance studies.- control_series_results_v7.csv: Time-series control data for misinformation/disinformation studies.- yearly_counts_v6.csv & control_series_results_v6.csv: Comparative series (using type:article filter) for sensitivity analysis.- attention_tracking_v6_typefix.py & control_series_v6_typefix.py: Python scripts for OpenAlex API data extraction and exact substring matching.- diagnose_2025_anomaly.py: Python diagnostic tool evaluating OpenAlex 2025 indexing behavior and XPAC layer status.- README.md: Detailed replication guide.