Speak. Share. Thrive. A Retrospective Study of the Public Engagement Process for Alberta's Social Policy Framework
Bibliographic record
Abstract
This Capstone Project provides insight into public engagement practices and analysis of the Alberta Government’s Speak. Share. Thrive. engagement process. In an effort to address social policy issues facing Albertans, Alberta Human Services was mandated to create Canada’s first provincial Social Policy Framework. The Framework, released in 2013, was a direct outcome of input collected through the Speak. Share. Thrive. engagement process. This process collected input from over 31,000 Albertans over six months using a variety of different engagement techniques. Public contributions from employees, businesses, social services, community members, and families provided the content for this Framework, and will guide Alberta’s social policy initiatives over the next decade and beyond. This Capstone Project identifies public participation’s history and theory, the merits and difficulties of public engagement practices, as well as direct insight into the experiences of Speak. Share. Thrive.’s creators and participators. The analysis is centred on identifying best practices and gaps in the engagement process. It provides insight into advantages and challenges of Speak. Share. Thrive. and offers policy options to advance accomplishments and address barriers.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".