Prioritizing barriers and solutions to improve employment for persons with developmental disabilities
Bibliographic record
Abstract
Purpose: Persons with a developmental disability have the lowest rate of labour force participation relative to other disabilities. The widening gap between the labour force participation of persons with versus without disability has been an enduring concern for many governments across the globe, which has led to policy initiatives such as labour market activation programs, welfare reforms, and equality laws. Despite these policies, persistently poor labour force participation rates for persons with developmental disabilities suggest that this population experiences pervasive barriers to participating in the labour force.Materials and methods: In this study, a two-phase qualitative research design was used to systematically identify, explore and prioritize barriers to employment for persons with developmental disabilities, potential policy solutions and criteria for evaluating future policy initiatives. Incorporating diverse stakeholder perspectives, a Nominal Group Technique and a modified Delphi technique were used to collect and analyze data.Results: Findings indicate that barriers to employment for persons with developmental disabilities are multi-factorial and policy solutions to address these barriers require stakeholder engagement and collaboration from multiple sectors.Conclusions: Individual, environmental and societal factors all impact employment outcomes for persons with developmental disabilities. Policy and decision makers need to address barriers to employment for persons with developmental disabilities more holistically by designing policies considering employers and the workplace, persons with developmental disabilities and the broader society. Findings call for cross-sectoral collaboration using a Whole of Government approach.Implications for RehabilitationPersons with a developmental disability face lower levels of labour force participation than any other disability group.Individual, environmental and societal factors all impact employment outcomes for persons with developmental disabilities.Decision and policy makers need to address barriers to employment for persons with developmental disabilities holistically through policies guiding employers and broader societal behaviour in addition to those aimed at the individuals (such as skill development or training).Due to multi-factorial nature of barriers to employment for persons with developmental disabilities, policy solutions are wide-ranging and fall under the responsibility of multiple sectors for implementation. This calls for cross-sectoral collaboration using a “Whole of Government” approach, with shared goals and integrated responses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".