The Battle for Intellectual Freedom: Book Censorship in Canada and the United States
Bibliographic record
Abstract
Over the past three years, the American Library Association (ALA) and the Canadian Federation of Library Associations (CFLA) have documented an unprecedented exponential rise in book banning and censorship efforts across the United States and Canada. This surge has led to more books being permanently removed from collections across all types of libraries—most predominately in public and school libraries—and has intensified debates over intellectual freedom, a fundamental principle of libraries and democratic societies. A disproportionate number of challenged books contain BIPOC and 2SLGBTQ+ content, reflecting the growing right-wing moral panic concerned with protecting children from topics deemed “inappropriate” like diversity, gender and sexuality. The rise of organized, systematic, and legislative efforts to censor books, driven by " parental rights" groups, highlight the intersection of politicalpolarization, with conservative elected officials advancing bills to restrict access to diverse materials, particularly in the United States. In response, Library and Information Studies (LIS) professionals must develop robust policies, advocate for intellectual freedom, and engage in community dialogue to defend diverse collections. Events like the CFLA’s Freedom to Read Week and the ALA’s Banned Books Week play a crucial role in resisting censorship, and professional advocacy and political engagement remain essential tools in upholding intellectual freedom. Overall, LIS professionals must engage in advocacy and public education at local, organizational, provincial/state, and federal levels to oppose book banning and promote awareness of the fundamental principle of intellectual freedom.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.046 | 0.016 |
| Scholarly communication | 0.019 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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 source (direct Gemma or distilled Codex), 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".