Implementation of supported employment in the context of a national Canadian program: Facilitators, barriers and strategies.
Bibliographic record
Abstract
OBJECTIVE: To describe facilitators, barriers, and strategies to implementation of the Canadian national At Work/Au travail program. This program funded supported employment services, following some of the principles of the Individual Placement and Support (IPS) model, in 12 sites across Canada. METHOD: We conducted on-site individual interviews (12) and focus groups (15) with 35 employment support workers, 12 team supervisors or managers, and 10 directors or CEOs. Interview summaries were created and coded using thematic analysis techniques. Codes were then distilled into themes grouping prominent barriers and facilitators to implementation. RESULTS: Four themes emerged: (i) national program structure: Flexible eligibility criteria and flexibility in use of subsidy funds were perceived as generally helpful, although there were difficulties associated with communication around noneligibility decisions and outcome targets; (ii) training and reinforcement: The support provided to sites was generally thought to be an important facilitator, especially when more intensive. Several participants viewed the online IPS training as a facilitator; (iii) external factors: Rules concerning impacts of employment earnings on benefits could be viewed as a barrier; and (iv) internal factors: Facilitators included strong leadership, positive staff attitudes, and larger program size. Several participants reported staff resistance as a barrier. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: Several features of the national program structure and leadership emerged that could be maintained if the program were extended elsewhere. The flexibility allowed for spending of wage subsidy funds, as well as the provision of more intensive training, were both perceived as potential enhancements to an eventual expansion of the program. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".