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Record W2092286976 · doi:10.1108/02641611211214297

How copyright affects interlibrary loan and electronic resources in Canada

2012· article· en· W2092286976 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInterlending & Document Supply · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInterlibrary loanLicenseCopyright lawBusinessLoanFair useLibrary scienceComputer sciencePolitical scienceIntellectual propertyLawFinance

Abstract

fetched live from OpenAlex

n Canada, the Copyright Act, copyright collectives such as Access Copyright, and the terms of negotiated license agreements all affect library practice. This paper will discuss how interlibrary loan practices and access to electronic resources are influenced by these three factors. For example, the Copyright Act does not allow digital interlibrary loan. Neither does the recent interim Access Copyright tariff, but the 2004 CCH Supreme Court Judgment seems to allow libraries a path forward for digital interlibrary loan. How do Canadian libraries choose between these conflicting messages? One of the biggest licensing issues facing Canadian libraries are electronic licenses that require Canadian libraries to follow American rather than Canadian copyright law. Two such examples are the CONTU guidelines and section 108 (g) (2) of US Copyright Law. There is nothing equivalent to section 108 (g) (2) in Canadian law, yet it is not uncommon to find Canadian libraries that have signed licenses requiring them to follow this and other parts of American law. How do Canadian libraries deal with conflicting requirements between the license and Canadian law?

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScholarly communication
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: yes
Not applicablelow
gptScholarly communication
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: yes
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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