Community Services Council of Newfoundland
Bibliographic record
Abstract
The Community Services Council of Newfoundland and Labrador was delighted to enter into a joint undertaking with Human Resources Development Canada (HRDC), Newfoundland Region, to take advantage of the Policy Internships and Fellowships Program (PIAF). The program was designed to enable a federal employee to spend several months with a voluntary, community-based organization. One of the outcomes of the federal Voluntary Sector Initiative, PIAF presented a wonderful opportunity for a government agency and a non-profit organization to work cooperatively on a policy project of mutual interest and import. Our theme focused on a longstanding perception that the further one gets from the centre of Canada the more difficult it is to influence major policy directions. While this perception was much talked about, it was the Community Services Council’s objective to determine if the perception was founded and if so, to what extent. This was an ambitious undertaking which set out to address the level of influence and involvement in the policy- making process of “regions on the periphery”. Traditionally, the regions (both government and the voluntary, community-based sector) have been “consumers and recipients ” of policy. As well, we wanted to explore mechanisms to enable regions on the periphery to be more directly involved in shaping public
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.076 | 0.009 |
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".