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Record W2209307390 · doi:10.17583/qre.2015.1418

Mature Students Speak Up: Career Exploration and the Working Alliance

2015· article· en· W2209307390 on OpenAlexaff
Terilyn Pott

Bibliographic record

VenueQualitative Research in Education · 2015
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsAlliancePsychologyInterpersonal communicationCritical Incident TechniqueExploratory researchCareer counselingMedical educationPopulationEducational institutionCareer portfolioInstitutionProcess (computing)Career developmentPedagogyApplied psychologySocial psychologyManagementMedicineSociology

Abstract

fetched live from OpenAlex

This exploratory study was undertaken to learn more about how mature students perceive the career counselling process in a post-secondary institution. Through the use of critical incident technique this study examined how three mature students interpret their relationship between themselves and their counsellors. Significant factors identified as contributing to a positive interpersonal connective bond were considering the whole of the clients’ experience, integrating career and personal concerns, introducing assessment tools appropriately, and utilizing counsellor self-disclosure appropriately. This study highlights the importance of utilizing critical incident technique in career counselling, the importance of the working alliance for mature students, and identifies possible counselling applications to consider when working with this population.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.542
GPT teacher head0.630
Teacher spread0.088 · 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 designQualitative
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

Citations3
Published2015
Admission routes1
Has abstractyes

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