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Record W6983268145

Marketing professional publications to the post-secondary education market: a case study of the publications of the Centre for Addiction and Mental Health

2011· other· en· W6983268145 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2011
Typeother
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthAddictionMandatePublishingRelevance (law)Value (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

The publishing division of the Centre for Addiction and Mental Health (CAMH) aims to increase the use of its professional books as course texts in colleges and universities by conducting marketing activities in this area. The report looks at CAMH’s role as a publisher, including the relevance of its mandate and publications to this post-secondary market. It then reviews CAMH’s past marketing approaches and strategies of other publishers who market to the post-secondary market. In order to gain a better understanding of CAMH’s educational market, a survey was conducted among 29 instructors of post-secondary mental health and addiction courses to determine how they choose and use their course texts. Findings showed that course texts are an important part of the learning curriculum; that instructors value Canadian-based texts that are closely aligned to course topics; and that instructors are generally open to receiving information from publishers.

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)0.007
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0140.006
Scholarly communication0.0150.006
Open science0.0020.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.019
GPT teacher head0.266
Teacher spread0.246 · 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 designCase report
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
Published2011
Admission routes1
Has abstractyes

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