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Making Career Theories More Culturally Sensitive: Implications for Counseling

2007· article· en· W2032219118 on OpenAlexaff
Richard A. Young, Sheila K. Marshall, Ladislav Valach

Bibliographic record

VenueThe Career Development Quarterly · 2007
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCulturally sensitiveAction (physics)Value (mathematics)PsychologyConceptual frameworkCareer counselingSocial psychologyEpistemologyApplied psychologySociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

The primary question addressed in this article is whether and how career theories can be more culturally sensitive without losing value as conceptual explanations or their usefulness for counselors. Contextual action theory is identified as a means to develop culturally sensitive explanations. Six steps are proposed and illustrated, including using the naive observations and subjective reports and recognizing ongoing processes. The use of these steps in counseling is also addressed.

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)0.072
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.072
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0720.123
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.035
Scholarly communication0.0130.018
Open science0.0040.013
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.0060.001

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 head0.059
GPT teacher head0.357
Teacher spread0.297 · 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 designTheoretical or conceptual
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

Citations61
Published2007
Admission routes1
Has abstractyes

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