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Record W4407943055 · doi:10.18357/ijcyfs154202422219

MEETING THE EMPLOYMENT NEEDS OF MARGINALIZED YOUTH: A REVIEW OF PROMISING YOUTH EMPLOYMENT PROGRAMS

2024· review· en· W4407943055 on OpenAlexafffundvenueabout
Alexandra Youmans, Alicia Hussain, Lorraine Godden, Benjamin Kutsyuruba, Alana Butler, Christopher DeLuca, Samantha Shewchuk

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2024
Typereview
Languageen
FieldSocial Sciences
TopicYouth Education and Societal Dynamics
Canadian institutionsCarleton UniversityConference Board of CanadaQueen's University
FundersMinistry of Advanced EducationMinistry of Advanced Education and Skills Development
KeywordsSociologyEconomic growthLabour economicsCriminologyPolitical scienceEconomics

Abstract

fetched live from OpenAlex

The Youth Job Connection program in Ontario, Canada is designed to help multi-barriered youth transition into the workforce. As part of an evaluation of the program, a review of comparable employment programs in Canada and similar English-speaking countries was conducted, which involved 57 national and 36 international programs. The purpose of the review was to identify promising programs and explore how they support the successful transition of NEET (not in education, employment, or training) youth into the labour market. A major finding was that promising youth employment programs not only address the work needs of marginalized youth, but also life skills and life stabilization. Such programs incorporate pre-employment training, mentoring and job coaching, paid work placements, life skills training, and life stabilization supports. Life stabilization supports varied across programs, with different amounts and types offered; further research is needed to determine what life stabilization supports best help NEET youth to secure and maintain employment. Considerations for improving the quality of employment programs for NEET youth are discussed. Lastly, given that NEET youth are not a homogeneous group, youth employment programs should target subpopulations of NEET youth, like those that are marginalized.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.371
Threshold uncertainty score0.851

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.144
GPT teacher head0.416
Teacher spread0.272 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreReview

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

Citations2
Published2024
Admission routes4
Has abstractyes

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