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Record W4309923991 · doi:10.1177/10690727221141983

Trajectories of Change in Career Decision Difficulties During a Manualized Individual Career Counseling Intervention: The Influence of Counselor Adherence, Working Alliance and Client Personality Traits

2022· article· en· W4309923991 on OpenAlexafffund
Francis Milot‐Lapointe, Yann Le Corff

Bibliographic record

VenueJournal of Career Assessment · 2022
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversité de Sherbrooke
FundersFonds de Recherche du Québec-Société et Culture
KeywordsPsychologyIntervention (counseling)AllianceCareer counselingNeuroticismBig Five personality traitsPersonalityClinical psychologyApplied psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

This study aimed to identify trajectories of change in client career decision difficulties during a manualized career counseling intervention and examine the role of counselor adherence, working alliance, and personality traits in predicting these trajectories. Participants were 257 individuals who received an average of 7.79 career counseling sessions at a university career services center. Using growth mixture modeling, four class-trajectories were identified. Clients in class 1 had a moderate level of decision difficulties at the beginning of counseling while clients in classes 2, 3 and 4 had moderate-salient initial levels of difficulties. Clients in classes 1 and 2 experienced a very large reduction of their decision difficulties during counseling and left the process with negligible levels of difficulties. Clients in class 3 saw a large reduction of their decision difficulties during counseling and left the process with moderate levels of difficulties. Clients in class 4 did not experience change and left the process with moderate-salient levels of difficulties. Counselor adherence to the intervention manual significantly contributed to discriminate between clients from class 4 and clients from classes 1, 2 and 3. Client level of neuroticism significantly contributed to distinguish clients belonging to class 4 from clients belonging to class 1.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.094
GPT teacher head0.372
Teacher spread0.278 · 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.

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

Citations6
Published2022
Admission routes2
Has abstractyes

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