The ideal of consumer choice in social services: challenges with implementation in an Ontario injured worker vocational retraining programme
Bibliographic record
Abstract
PURPOSE: Social service programmes that offer consumer choices are intended to guide service efficiency and customer satisfaction. However, little is known about how social service consumers actually make choices and how providers deliver such services. This article details the practical implementation of consumer choice in a Canadian workers' compensation vocational retraining programme. METHOD: Discourse analysis was conducted of in-depth interviews and focus groups with 71 injured workers and service providers, who discussed their direct experience of a vocational retraining system. Data also included procedural, policy and administrative documents. RESULTS: Consumer choice included workers being offered choices about some service aspects, but not being able to exercise meaningful discretion. Programme cost objectives and restrictive rules and bureaucracy skewed the guidance provided to workers by service providers. If workers did not make the "right" choices, then the service providers were required to make choices for them. This upset workers and created tension for service providers. CONCLUSIONS: The ideal of consumer choice in a social service programme was difficult to enact, both for workers and service providers. Processes to increase quality of guidance to social service consumers and to create a systematic feedback look between system designers and consumers are recommended. Implications for Rehabilitation Consumer choice is an increasingly popular concept in social service systems. Vocational case managers can have their own administrative needs and tensions, which do not always align with the client's choices. Rehabilitation programmes need to have processes for considering what choices are important to clients and the resources to support them.
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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 | 0.070 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.033 | 0.045 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".