A Needs Assessment for a Local Social Policy Data Sharing Program
Bibliographic record
Abstract
Planners seek collaborative and diverse strategies to address complex challenges across Canada. In the Region of Waterloo, local governments and stakeholders adopted The Waterloo Region Community Data Program (WRCDP), a social policy data-sharing system for information on economic and social development. This study examined the needs of Community Data Program (CDP) users to investigate whether CDPs are utilized effectively. We considered how optimal use of CDP data may advance planning to resolve structural and behavioral challenges in municipalities. We surveyed 17 participants from the WRCDP to assess needs of organizational members regarding accessing data, data analysis, and networking. Participants expressed enthusiasm for the CDP’s potential but lacked training in accessing and analyzing available data. A limitation of this study is small participant sample size and how results may not be generalizable to other locations. Organizational members remained optimistic about the system’s potential for planning and policy when provided with the necessary support.
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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 | 0.034 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.017 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| 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".