Demography of Censorship: Examining Correlations Between Community Demographics and Materials Challenges in Canadian Libraries
Bibliographic record
Abstract
This study examines materials challenges in Canadian libraries, compiled by the Canadian Federation of Library Associations (CFLA), with the intention of identifying demographic trends in patron challenge behaviour. By cross-referencing the CFLA data with five demographic fields from the 2016 Canadian census of population (median age, city size, educational attainment level, median income, and political representation), the study aims to determine whether challenges of a certain nature are more likely to occur in communities with certain demographic profiles. The study identifies twenty-two challenge categories derived from user complaints and three ideological alignments of challenges based on the political ideology standards set by moral foundations theory. Though the available sample is too small to draw any definitive conclusions, some strong trends were apparent. Findings show that the most common challenge types, challenges to racist content and sexual content, are fairly consistent throughout demographic groupings, but notable correlations were found between demographic profiles and materials concerning LGBTQIA+ issues. Progressive-leaning communities were far more likely to challenge homophobic/transphobic materials while conservative-leaning communities challenged more LGBTQIA+-positive works. From an ideological standpoint, young communities tend to be the most progressive in their challenge behaviour, while communities with a low level of educational attainment tend to be the most conservative in their challenge behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.023 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".