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Record W7124366601

The Invisibility of TPMs in Academic Libraries How Digital Content Protection Has Become Part and Parcel of Platform Design

2025· article· W7124366601 on OpenAlexaboutno aff
Anthony D Rosborough, Katherine Silins

Bibliographic record

VenueeYLS (Yale Law School) · 2025
Typearticle
Language
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsnot available
Fundersnot available
KeywordsInvisibilityDigital rights managementDigital contentFair useIntellectual propertyContent analysis
DOInot available

Abstract

fetched live from OpenAlex

This article investigates a growing divide in how TPMs are understood and encountered across two domains: digital content access and software-dependent device controls. Through legal and qualitative empirical lenses, it reveals that TPMs guarding digital content access across Canadian academic institutions (particularly relating to e-books, journals, and streaming media) have become seamlessly embedded into platform design and licensing schemes. This facilitates their ubiquity and invisibility, while at the same time making them difficult to challenge from a law and policy reform perspective. It also makes content TPMs difficult to identify, measure, or challenge in furtherance of lawful exceptions and limitations to copyright, even for information management professionals. By contrast, device TPMs (those locking down physical hardware through embedded software and firmware) have operated much more visibly and discretely, making them more amenable to legal and policy reform in recent years (e.g., through Bills C-244 and C-294). The article argues that this divergence has left policymakers and open knowledge advocates struggling to identify and remedy the impacts of content TPMs, despite the longstanding debates within copyright circles. Understanding this bifurcation is essential for crafting targeted future policy that can preserve users' legitimate access rights in furtherance of fair dealing and the exceptions and limitations to copyright. Cet article enquête sur l'écart croissant qui existe dans la façon que les mesures de protection technologiques sont comprises et rencontrées dans deux domaines: l'accès au contenu numérique et le contrôle des appareils qui dépendent de logiciel. Une revue de la situation à travers un cadre juridique et qualitatif démontre que les mesures de protection technologiques qui protègent l'accès au contenu numérique dans les institutions académiques canadiennes (surtout en ce qui traite de livres numériques, et les revues et les médias en diffusion) aient été intégrées de manière homogène dans la conception de plateforme et les systèmes d‘octroi de permis d‘utilisation. Cela facilite leur présence et invisibilité tout en rendent leur remise en cause difficile. De plus, cela rend le contenu des mesures de protection technologique difficile à identifier, mesurer ou à contester dans le cadre de l'application des exceptions et limitations juridiques au droit d'auteur, et ce même pour les experts en gestion d‘informatique. En revanche, les TPM des appareils (verrouillant le matériel physique grâce aux logiciels et micrologiciels intégrés) ont fonctionné de manière beaucoup plus visible et discrète. Ceci les a rendus plus favorables aux réformes juridiques et politiques au cours des dernières années (par exemple, par le biais des projets de loi C-244 et C-294). Cet dissertation soutient qu’à cause de cet écart les décideurs politiques ainsi que les défenseurs de la libre connaissance seraient aux prises avec la difficulté de cerner et remédier à l'impact des TPM de contenu, nonobstant les débats de longue date dans les milieux de droits d'auteur. Toute création de politique future ciblant la préservation des droits d'utilisateurs dans le cadre de l‘application de l'utilisation équitable et les limitations aux droits d‘auteur devrait être axée sur la compréhension de cette bifurcation

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.006
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.097
GPT teacher head0.242
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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