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Record W7042673689

Policy and evidence review on work transition interventions and work disruptions of post- secondary student graduates with disabilities: Insights for social and education policy

2016· article· en· W7042673689 on OpenAlexaboutno aff

Bibliographic record

VenueCommonKnowledge Research Repository (Pacific University Oregon) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionWork (physics)UnemploymentPublic policyGrey literatureActive labour market policiesSocial policyEmpirical evidence
DOInot available

Abstract

fetched live from OpenAlex

Statement of purpose: Despite completion of higher education, students with disabilities experience persistent underemployment, unemployment and delayed entry into work. Specifically, they experience long periods of work disengagement, lack of participation in valued or meaningful work, and loss of confidence in skills due to delays in finding work; all of which contribute to decreased self-worth, health, and wellbeing. These consequences underscore new areas of concern by governments and employers and the need to find new ways that policy and practices can minimize work occupation disruptions for youth. In 2013 Urbanowski and colleagues suggested that to promote work sustainability or mobility in times of economic challenge and globalization there is a need for social policy informed by concepts from occupational injustice, occupational salience, and the examination of the occupational ecosystem. Thus, the first aim of this review was to synthesize knowledge of work transitions interventions that support safe and effective entry into work, as well as work retention in the labour market for post-secondary student graduates. The second aim was to identify implications for informing policy and research. Methods: Arskey and O’Malley’s scoping review methodology (Arskey and O’Malley 2005) was used to search and synthesize data from evidence and policy databases (EMBASE, CINAL, SCOPUS, Pub Med, Canadian Public Policy Collection, Canadian Research Index, ERIC, Sociological Abstracts, PsychINFO/INFORM, Index to Foreign Legal periodicals, Proquest). DistillerSR and Excel supported document selection and management. Results: N=30 documents met the selection criteria. Synthesis of extracted data from 23 empirical studies and 7 grey literature documents and 20 websites identified that coordination of an array of targeted interventions will improve employment outcomes. The existence of policies or legislation to support employment equity or human rights are associated with less disruptions and easier entry into employment. Intervention components with promise include work experiences such as job placements and internships; labour market skills training; accommodation awareness and support; self-awareness and disclosure training; and mentorship.\nImplications: The current occupational ecosystem of employment resources and accommodation policies in the literature related to post- secondary graduates with disabilities is focused on becoming employed and on foundational skills. There is little attention on career supports after graduation or on global citizenship skills to support work sustainability or mobility in times of precarious employment. This presentation identifies key steps that are needed to open a social policy dialogue in higher education and employment supports and a research agenda to support improved work transitions and work sustainability for post-secondary graduates with disabilities.

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)0.032
metaresearch head score (Gemma)0.120
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.032
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.120
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0150.015
Science and technology studies0.0020.002
Scholarly communication0.0080.006
Open science0.0040.004
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0150.002

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 head0.137
GPT teacher head0.432
Teacher spread0.294 · 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 designSystematic review
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

Citations0
Published2016
Admission routes1
Has abstractyes

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