On the right tack? An evaluation of the ILRC’s able sail program
Bibliographic record
Abstract
Over the last century, the importance of providing quality services, using evidence-based strategies and demonstrating program results have become increasingly significant components of social work practice. This research project explores the role of assessing social service programs through the evaluation of Able Sail - an accessible sailing program managed by the Independent Living Resource Centre (ILRC) of Winnipeg. Through a review of previous research surrounding the importance of recreation and leisure engagement as a human right, the need for accessible programming is quickly established. Similarly, the need for evaluating social service programs is also explored in detail, along with evaluation models and challenges to implementation. Utilizing a Context, Input, Process and Product (CIPP) evaluation method, this project began by analyzing administrative documents provided by Able Sail. It then sought feedback from program participants, its staff members, and agency board members to better understand Able Sail’s impact and determine whether improvements could be made to better meet the needs of consumers. What was discovered is that many participants believe Able Sail to be a valuable program which provides many individuals the opportunity to engage in an inclusive leisure activity and enjoy the great outdoors. Not only did most respondents believe that the program helped sailors to build confidence and self-esteem, and enhance their independence, nearly all also agreed that the program helped them to feel better about themselves, build positive relationships with others and get involved with their community. That said, due to the limited data available, conclusive results are difficult to establish. Despite this, this project serves to shed light on some of the challenges faced in evaluating social service programs. It concludes by detailing the limitations of this evaluation and provides recommendations for future research.
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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 | 0.035 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".