MétaCan
Menu
Back to cohort
Record W2362317590 · doi:10.1177/1468017316649357

Youth unemployment: Implications for social work practice

2016· article· en· W2362317590 on OpenAlexaff
Jianqiang Liang, Guat Tin Ng, Ming‐sum Tsui, Miu Chung Yan, Ching Man Lam

Bibliographic record

VenueJournal of Social Work · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEmployabilityUnemploymentYouth unemploymentWork (physics)Social workYouth studiesSociologyPublic relationsEconomic growthPolitical scienceEconomicsPedagogyGender studies

Abstract

fetched live from OpenAlex

Summary This article discusses a missing but emergent role of social work with unemployed young people. The authors highlight the transitional and structural factors of youth unemployment. Using a social work lens, the “Youth Employment Network” (YEN) is discussed and the International Labour Organization’s “4Es” (employability, equal opportunity, employment creation, entrepreneurship) framework is elaborated. This article adds a fifth “E” (Ecological connection) and proposes a “5Es” model for social workers to support unemployed young people to overcome transitional and structure barriers for employment. Findings Limited social work programs, studies, or evaluations are targeted for unemployed young people despite historical concern with employment conditions of workers and suggest the instrumental role in research, policy and practice concerning the unemployed young people. Applications Recommendations are provided in terms of how to implement the 5Es in policy, education, training, and direct practice of social work in youth employment.

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)0.011
metaresearch head score (Gemma)0.013
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.005
Scholarly communication0.0060.003
Open science0.0010.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0080.000

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 head0.115
GPT teacher head0.452
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 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

Citations13
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Social WorkSame topicEmployment and Welfare StudiesFrench-language works237,207