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Record W2036660495 · doi:10.1177/1523422304266088

National Governance and Promising Practices in Workplace Learning: a Postindustrial Programmatic Framework in Canada

2004· article· en· W2036660495 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAdvances in Developing Human Resources · 2004
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsGovernment of Canada
Fundersnot available
KeywordsPost-industrial societyPublic relationsConstruct (python library)Context (archaeology)PhenomenonCorporate governanceHuman resourcesPolitical scienceSociologyEngineering ethicsKnowledge managementManagementEngineeringEconomicsEpistemology

Abstract

fetched live from OpenAlex

The problem and the solution. Implicitly or explicitly, the work of most human resource development (HRD) professionals contributes in some way to national purpose. Even in the private sector, a sense of national identity is not lacking in HRD products, processes, and programs, even though this phenomenon may not be readily apparent to either practitioners or researchers. Viewed through the practitioner’s lens of typical HRD interventions, national HRD (NHRD) as a construct favors a description of the historical evolution of current practices. In this article, this analysis is reversed so that national purpose and supporting policies are used as the lens to assess a possible future evolution of NHRD practices and programs in Canada that support workplace learning in a changing national context.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.619
Threshold uncertainty score0.965

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.363
Teacher spread0.319 · 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