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Record W2090428131 · doi:10.1080/00131881.2015.1030854

Preparing at-risk youth for a changing world: revisiting a person-in-context model for transition to employment

2015· article· en· W2090428131 on OpenAlexafffund
Christopher DeLuca, Lorraine Godden, Nancy L. Hutchinson, Joan Versnel

Bibliographic record

VenueEducational Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsDalhousie UniversityQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTransition (genetics)Context (archaeology)PsychologySociologySocial psychologyHistory

Abstract

fetched live from OpenAlex

Background: The current global cohort of youth has been called ‘a generation at-risk’, marked by a dramatic rise in youth who are not in employment, education or training programmes. In 2010, youth were three times as likely as adults to be unemployed, with youth unemployment worsening in 2012 and 2013. Accordingly, there is an urgent need to examine educational structures that can promote greater labour market attachment and successful transition into employment for youth worldwide. Vocational and work-based education (WBE) has been identified as one of the most recommended and promising educational structures for curtailing youth under- and unemployment. However, WBE takes many forms, making it difficult to discern which WBE programme is most likely to meet the diverse needs of any individual at-risk youth. Moreover, there has been a dearth of theoretical conceptualisations to explain WBE as a context that promotes resilience for at-risk youth as they transition into the world of work.Purpose: The purpose of this paper is to present a revised model for WBE as an enabling context for at-risk youth in transition from school to employment. Specifically, a person-in-context approach is used, situating youth-related facets (e.g. agency) in relation to systemic facets (e.g. political, cultural) to provide a comprehensive theoretical basis for WBE. The revised model maintains three overlapping domains – the individual, the social-cultural and the economic-political – to address a theoretical gap in the literature on transition systems while providing a foundation for practical efforts to prepare at-risk youth for engaging in a changing labour market.Design and Methods: The model was constructed through a systematic and interdisciplinary integrative literature review that examined empirical, conceptual, policy-based and practice-based literature on at-risk youth transition from school to work. Articles and documents were analysed for both individual and contextual factors that influence transition, in order to contribute towards the development of a robust person-in-context model. Existing models of transition and other systems were also examined that addressed the needs of at-risk youth. A ‘person-in-context’ approach was selected for our model as it enabled representation of both macro- and microcosmic factors that shape effective WBE programming.Conclusions: The model is organised around three critical domains that were identified as being influential for school-to-work transition: the individual domain, the social-cultural domain and the economic-political domain. Within each of these domains, multiple facets are described that shape youth transition. WBE is positioned at the centre of the model as an educational structure that can attend to the multiple facets that shape engagement in school and work. The paper concludes with an explicit research agenda linked to the model and practical implications for WBE programming.

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)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.018
Scholarly communication0.0100.012
Open science0.0030.013
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.297
GPT teacher head0.477
Teacher spread0.179 · 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 designQualitative
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

Citations18
Published2015
Admission routes2
Has abstractyes

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