Assessing the Needs of Agency Stakeholders With Regards to the Development of a Community Employment Initiative
Bibliographic record
Abstract
Background: In light of the current directives of the Ontario Ministry of Community and Social Services (MCSS) towards providing more inclusive employment opportunities and closure of sheltered workshops, service providers are working to shift their employment services to be more community-based. This study investigated the needs of clients in one community agency, their caregivers, agency staff and administration, regarding the development of a community-based employment program for service users with intellectual and developmental disabilities (IDD). Methods: This qualitative case study used a needs assessment framework based on the model developed by Witkin and Altschuld (1995). Prior the start of the data collection, a pre-assessment was conducted which provided the background and premise for the current assessment. The full needs assessment included four participant groups: agency clients, caregivers, day program staff and senior management. Clients and their caregivers participated in individual, semi structured interviews. Day program staff and senior management participated in separate focus groups. Results/Discussion: This evaluation determined that all stakeholders would like community-based employment services to be offered by the agency, and clients expressed an interest in supported employment services, vocational services and a social enterprise. The results of this assessment also highlight factors that impact stakeholders’ motives for pursuing community based employment services, and the organizational and structural barriers that hinder the agency’s development of such services. Due to the diversity in the clientele, there was ambivalence amongst stakeholders about which type of employment program will best suit service users and the organization overall.
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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 | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 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".