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Record W4391263567 · doi:10.53379/cjcd.2024.385

Professionalizing the Canadian Career Development Sector: A Retrospective Analysis

2024· article· en· W4391263567 on OpenAlexaffvenueabout
Lorraine Godden, Roberta Borgen

Bibliographic record

VenueCanadian Journal of Career Development · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsCarleton University
Fundersnot available
KeywordsCareer developmentPolitical scienceSociologyPedagogy

Abstract

fetched live from OpenAlex

The Canadian career development sector has worked for decades to enhance the professionalization of career development professionals, with such projects as the original standards and guidelines (S&Gs) launched in 2001. However, to reflect and guide current practice, extensive updates and a new approach were needed. Through research, consultation, development, and validation, the Pan-Canadian Competency Framework for Career Development Professionals, the National Competency Profile for Career Development Professionals, and the Code of Ethics for Career Development Professionals were created. In examining the process of this comprehensive project, Bronfenbrenner’s (1979) ecological systems theory offers a conceptual framework for understanding the complex interconnected systems impacting the sector. Then Kouzes and Posner’s (2003, 2012) five exemplary practices of leadership are applied to explore the actions and behaviours that created purposeful spaces where practitioners, subject matter experts, and theorists could collectively and authentically work together to accomplish extraordinary tasks.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.784

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.023
Science and technology studies0.0180.004
Scholarly communication0.0060.002
Open science0.0030.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.230
Teacher spread0.196 · 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 designObservational
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
Published2024
Admission routes3
Has abstractyes

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