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Record W2005831673 · doi:10.1080/0046760x.2013.834523

‘Fratricidal warfare’: English-Canadian textbook publishers take on the Americans, 1970–1980

2013· article· en· W2005831673 on OpenAlexaffabout
Penney Clark, Wayne Knights

Bibliographic record

VenueHistory of Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPublishingRevenuePolitical scienceSociologyMedia studiesLawEconomics

Abstract

fetched live from OpenAlex

Educational publishing sits at the intersection of industry, culture and education. Pedagogical aims must be balanced with the need for publishers to make a profit, while also acknowledging Canadian national identity and culture. The events of central interest are related to the tensions between two publishers’ associations in the wake of the sales, in 1970, of Canadian publishers Gage and Ryerson Press to American interests. The Canadian Book Publishers’ Council was comprised mainly of American branch plants and the Independent Publishers Association membership was Canadian-owned publishing companies. The two associations became bitter rivals, engaging in ‘fratricidal warfare’, as they lobbied the provincial and federal governments and fought to maintain their places in the textbook market. About 65% of total sales revenues from publishing in Canada came from textbook sales in this period. Both governments and commercial interests had to balance Canadian sovereignty with commercial gain and educational goals.

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 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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0250.012
Scholarly communication0.0100.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.223
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2013
Admission routes2
Has abstractyes

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