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Record W2973848690 · doi:10.82396/cjcd.v17i2.3133

Career and Guidance Counsellors Working in French Language Secondary Schools in Ontario: An Inventory of Current Tasks and Perceived Competence

2020· article· en· W2973848690 on OpenAlexaffabout
André Samson

Bibliographic record

VenueCorpus Université Laval (Université Laval) · 2020
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversité du Québec à MontréalUniversité LavalUniversity of Ottawa
Fundersnot available
KeywordsCompetence (human resources)PsychologyMedical educationCareer counselingPedagogyJurisdictionMedicinePolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

In a North-American context, the practice of career and guidance counselling is plagued with many issues depending on jurisdiction. Usually those issues are related to the fact that career and guidance counsellors are obliged to engage in practices that are not always related to their profession. Considering the fact that career and guidance counsellors in Ontario are mainly teachers with little formal education and no clinical training, the current study’s objective was to identify, describe, and conceptualize the tasks accomplished by N = 73 career and guidance counsellors working in French-language secondary schools in Ontario. Results suggest that career and guidance counsellors in Ontario spend a great deal of time on tasks unrelated to career and guidance counselling. Furthermore, a correlation between the amount of time allocated to, and the perceived level of competence in, completing some of the daily tasks accomplished by participants was identified. Finally, results suggest that career and guidance counsellors in Ontario often perceive themselves as being incompetent when it comes to some of the essential tasks associated with career and guidance counselling.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.029
GPT teacher head0.245
Teacher spread0.216 · 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 teacher head, not a consensus.

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

Citations1
Published2020
Admission routes2
Has abstractyes

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