Locked Out: An Empirical Study of the Impacts of Technological Protection Measures on Digital Content Access in Canadian Academic Libraries
Bibliographic record
Abstract
This report presents findings from a comprehensive empirical qualitative study involving interviews with Canadian academic librarians, copyright officers, and information professionals to examine how TPMs affect digital content access. The research reveals that TPMs are deeply embedded within the technology and licensing frameworks used by libraries, creating opaque barriers to lawful access. Practitioners often lack clarity on whether restrictions stem from TPMs or from contractual or platform design, complicating their ability to support fair dealing uses of works, preservation, and teaching. This ambiguity has increased substantially with the rise of controlled digital lending (CDL) and other access models that have accelerated since the COVID-19 pandemic. The study documents how this ambiguity leads to caution, workarounds, and self-censorship, even when legal rights exist. These findings highlight significant challenges in reforming content TPM policy within Canadian copyright law and underscore the need for legislative and regulatory clarity to support equitable access to scholarly and cultural materials. Final report added 07/10/2025.
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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 | 0.015 | 0.079 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.033 | 0.018 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".