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Record W2167291675 · doi:10.33524/cjar.v15i2.140

MOVING FORWARD ON A NATIONAL STRATEGY FOR DEVELOPING ESSENTIAL SKILLS

2015· article· en· W2167291675 on OpenAlexaffvenueabout
Maurice Taylor, Suzanne Taschereau

Bibliographic record

VenueThe Canadian Journal of Action Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAction researchParticipatory action researchPsychological interventionCitizen journalismMedical educationKey (lock)Action (physics)Knowledge managementPolitical sciencePedagogyPsychologyPublic relationsSociologyComputer scienceMedicine

Abstract

fetched live from OpenAlex

This pan Canadian participatory action research project involved faculty and managers in twelve Canadian colleges and institutes, nine employers, and 1300 students and workers in examining exemplary practice in essential skills as a way of catalyzing system change. Multiple sources of data were used in the three year project and key findings included: (1) the advance of a new knowledge system that documented an integrated approach to developing essential skills; (2) a culture shift that moved towards rigorous needs analysis and evidence based interventions in technical training programs; and (3) integration and ownership of essential skills in college programming.

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)0.034
metaresearch head score (Gemma)0.028
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: Other · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score0.446

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0110.006
Scholarly communication0.0060.004
Open science0.0040.014
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.380
GPT teacher head0.541
Teacher spread0.161 · 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
GenreOther

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

Citations2
Published2015
Admission routes3
Has abstractyes

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