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Record W4238249047 · doi:10.22215/etd/2017-12117

Early Predictors of Work Life Quality: A Longitudinal Analysis of the Transition from School to Work

2017· dissertation· en· W4238249047 on OpenAlexaffabout
Amy Ramnarine

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsCarleton University
Fundersnot available
KeywordsSchool-to-work transitionWork (physics)PsychologyQuality (philosophy)Developmental psychologyLongitudinal studyEducational leadershipJob satisfactionTransition (genetics)Social psychologyPedagogyMedicine

Abstract

fetched live from OpenAlex

The goal of the current study was to explore the early antecedents of three facets of work life quality: job satisfaction, income satisfaction, and leadership emergence.Using Statistics Canada's Youth in Transition Survey (YITS), the role of early leadership experiences, nurturing parenting, and parental work experiences on quality of work life was examined in two samples of Canadian youth followed between the ages of 15-25: (1) youth whose highest level of education was high-school or below, and (2) youth who pursued education at the post-secondary level.Overall, results supported the notion that early experiences and educational pathways play a role in shaping work life quality across the lifespan.While exposure to leadership in adolescence was associated with a young adult's later emergence into leadership roles, nurturing parenting and social support held distinct implications for a young person's entry to the world of work.Results have implications for research and practice.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.977

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.042
GPT teacher head0.342
Teacher spread0.299 · 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
Published2017
Admission routes2
Has abstractyes

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