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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 OpenAlexaffabout
Robert Tiessen

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.

How this classification was reachedexpand

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.978

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.009
Science and technology studies0.0210.012
Scholarly communication0.0150.005
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.001

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

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

Scholarly communication

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
Domainnot available
GenreEmpirical · Other

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

Citations9
Published2012
Admission routes2
Has abstractyes

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