MétaCan
Menu
Back to cohort
Record W2768171757 · doi:10.13152/ijrvet.4.3.3

Decision-Making Rationales among Quebec VET Student Aged 25 and Older

2017· article· en· W2768171757 on OpenAlexaffabout
Louis Cournoyer, Frédéric Deschenaux

Bibliographic record

VenueInternational Journal for Research in Vocational Education and Training · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à Montréal
Fundersnot available
KeywordsVocational educationContext (archaeology)Thematic analysisPsychosocialPsychologyValue (mathematics)Medical educationRelevance (law)PedagogySociologyQualitative researchGerontologyMedicinePolitical scienceSocial science

Abstract

fetched live from OpenAlex

Each year, a large number of students aged 25 years and over take part in vocational and education training (VET) programs in the Province of Quebec, Canada. The life experiences of many of these adults are marked by complex psychosocial and professional events, which may have influenced their career decision-making processes. This paper aimed to identify key rationales guiding the decisions of adults aged 25 years and older to return to education based on a thematic analysis of 30 semi-structured interviews with students enrolled in a VET program. The analysis focused on two theoretical axes: one biographical and the other interactionist. The first involved personal life courses and professional projects undertaken by the student in the past. The second examined tensions and conflicts between context forces and adjustment strategies adopted by the student. The results revealed five decision-making rationales that characterized the vast majority of the students’ experiences: 1) get out of a socioprofessional and economic slump; 2) know yourself better, personally and socially; 3) value the concrete and the practical; 4) take advantage of supporting conditions; and 5) reconcile proximity and the known. The relevance and implications of these findings for professionals and decision makers in vocational training 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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.001
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 head0.218
GPT teacher head0.555
Teacher spread0.337 · 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.

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

Citations4
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal for Research in Vocational Education and TrainingSame topicCareer Development and DiversityFrench-language works237,207