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Record W7046898717

For the Encouragement of Learning: The Origins of Canadian Copyright Law

2023· article· en· W7046898717 on OpenAlexaboutno aff

Bibliographic record

VenueProject Muse (Johns Hopkins University) · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsCopyright lawGovernment (linguistics)Public domainNormativeLegislative historyLegal historyPublic interestPublic policy
DOInot available

Abstract

fetched live from OpenAlex

For the Encouragement of Learning addresses the contested history of copyright law in Canada, where the economic and reputational interests of authors and the commercial interests of publishers often conflict with the public interest in access to knowledge. It chronicles Canada’s earliest copyright law to explain how pre-Confederation policy-makers understood copyright’s normative purpose.\nUsing government and private archives and copyright registration records, Myra Tawfik demonstrates that the nineteenth-century originators of copyright law intended to promote the advancement of learning in schools by encouraging the mass production of educational material. The book reveals that copyright laws were integral features of British North American education policy and highlights the important roles played by teachers, education reformers, and politicians in the emergence and development of the laws. It also explains how policy-makers began to consider the relationship between copyright and cultural identity formation once British interference into domestic copyright affairs increased, and as Canadian Confederation neared. Using methodologies at the intersection of legal history and book history, For the Encouragement of Learning embeds the copyright legal framework within the history of Canada’s book and print culture.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.235
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2023
Admission routes1
Has abstractyes

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