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Record W4392992716 · doi:10.4324/9781032633503-2

The effect of a career development programme based on the Hope-Action Theory: Hope to Work for refugees in British Columbia

2024· book-chapter· en· W4392992716 on OpenAlexaboutno aff
Hyung Joon Yoon, Natasha Bailey, Norman E. Amundson, Spencer G. Niles

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsnot available
Fundersnot available
KeywordsRefugeeWork (physics)Action (physics)Career developmentPsychologySociologyPolitical sciencePedagogyEngineeringLawMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

The purpose of this study was to assess the proximal and distal outcomes of a career development training programme for refugees that was developed based on the Hope-Action Theory (HAT). Adopting an experimental design, proximal outcomes such as self-efficacy, hope-action competencies, job search clarity, and career adaptability were assessed three times; and distal outcomes including employment status, job-seeking activities, career growth, hopeful career state, work engagement, and job satisfaction were assessed once at nine months. We used a two-way mixed effects analysis of covariance and a serial mediation analysis. The programme was effective in developing hope-action competencies, general self-efficacy, and job search clarity. The experimental group participants exhibited higher hopeful career state and work engagement. A serial mediation model of the HAT-based intervention predicting job satisfaction was found. Limitations and future directions 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.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.812
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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