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Record W4386568562 · doi:10.29173/pathfinder77

Abandoned But Not Forgotten

2023· article· en· W4386568562 on OpenAlexaffvenueabout
Elisa Kuhn

Bibliographic record

VenuePathfinder A Canadian Journal for Information Science Students and Early Career Professionals · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCopyright and Intellectual Property
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)Set (abstract data type)Work (physics)Orphan drugLaw and economicsCultural heritageCopyright lawPolitical scienceComputer scienceInternet privacyLawBusinessSociologyHistoryIntellectual propertyEngineering

Abstract

fetched live from OpenAlex

Under Canadian copyright law, archives and other cultural heritage institutions (CHIs) cannot legally share and distribute any orphan works in their collections. Orphan works are copyrighted materials whose copyright holders cannot be located or identified. To prove that a work is truly orphaned, the proposed user must demonstrate that the copyright holders could not be located after a diligent search. The burden of this rights clearance increases for CHIs that have large collections of orphan works. This paper reviews the current legal context for using orphan works in Canada, and the shortcomings. I propose a new system for orphan works rights clearance based on two parts. Firstly, formalizing the requirements for a diligent search to make them clear and objective. Secondly, creating a less stringent set of requirements specifically for use by CHIs, so that it is feasible for them to do diligent searches for large collections of materials. This paper also discusses and refutes multiple arguments against the proposed system.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0030.009
Open science0.0010.000
Research integrity0.0000.000
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 head0.062
GPT teacher head0.304
Teacher spread0.242 · 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 designObservational
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
Published2023
Admission routes3
Has abstractyes

Explore more

Same venuePathfinder A Canadian Journal for Information Science Students and Early Career ProfessionalsSame topicCopyright and Intellectual PropertyFrench-language works237,207