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Record W3130624513 · doi:10.1177/0894845321991648

Job Seekers’ Self-Directed Learning Activities Explained Through the Lens of Regulatory Focus

2021· article· en· W3130624513 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Career Development · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsBrock University
Fundersnot available
KeywordsRegulatory focus theoryAutodidacticismPromotion (chess)SeekersPsychologyContext (archaeology)Social psychologySelf-efficacyAffect (linguistics)PedagogyPolitical science

Abstract

fetched live from OpenAlex

This study aimed to understand the role of regulatory focus for influencing self-directed learning activities during a job search. The authors surveyed 185 job-searching university students at two time points to explore the conditions under which regulatory focus (promotion and prevention foci) impacts self-directed learning activities and the number of employment interviews secured. Both promotion and prevention foci showed significant relationships with self-directed learning activities and number of interviews, and positive and negative affect partially mediated these relationships. The relationships between both regulatory focus strategies and self-directed learning were also contingent on self-efficacy. More specifically, prevention focus and self-directed learning showed a positive relationship for job seekers with high levels of self-efficacy but a negative one for job seekers with low levels of self-efficacy. This research extends the understanding of the role of regulatory focus in the context of self-directed learning during a job search. Implications for research and practice are discussed.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.417

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.214
Teacher spread0.195 · 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