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Record W1796723269 · doi:10.21225/d54g6f

A Comparison of the Organizational Frameworks of Canadian and American University Continuing Education Units

2008· article· en· W1796723269 on OpenAlexaffvenueabout
Lorraine Carter, Chris Dougherty, Edna Wilson

Bibliographic record

VenueCanadian Journal of University Continuing Education · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsLaurentian University
Fundersnot available
KeywordsRespondentContinuing educationModalitiesInstitutionHigher educationInstitutional researchPolitical sciencePublic relationsSurvey researchAssociation (psychology)Medical educationPsychologyLibrary scienceManagementSociologySocial scienceMedicineApplied psychologyLawEconomics

Abstract

fetched live from OpenAlex

In 2006, a study involving institutional members of the Canadian Association of University Continuing Education (CAUCE) was conducted by the CAUCE Information and Research Committee working in collaboration with the Research Committee of the Association of Continuing Higher Education (ACHE). The survey had been previously completed by institutional members belonging to ACHE in the United States. This paper describes the survey findings and offers possible explanations of important differences related to respondent profile, type of institution by funding, and the extent of credit programming offered by the responding institutions. Differences related to learning modalities are also discussed. Further joint surveys involving CAUCE and ACHE members as well as international research initiatives sponsored by the two organizations are recommended.

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)0.008
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.985

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.009
Science and technology studies0.0150.008
Scholarly communication0.0090.002
Open science0.0040.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.019
GPT teacher head0.265
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 designQualitative
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
Published2008
Admission routes3
Has abstractyes

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