Bibliographic record
Abstract
Following consultations with senior officials across federal departments, the PRI's Social Capital Project was formally launched in January 2003 at an interdepartmental meeting of Assistant Deputy Ministers responsible for policy and research. Carried out under the guidance of the PRI's Executive Director, Jean-Pierre Voyer, the project team at the outset consisted of Jeff Frank, Catherine Demers and Robert Judge. Lori Brooks later joined the team, providing assistance with research activities and event coordination. Sandra Franke, initially on part-time secondment from Statistics Canada, came aboard to work on measurement issues, later joining the PRI full time. Also contributing her expertise on issues of diversity was Jean Lock Kunz. This expertise was applied during the development of the international conference on social capital, immigrant integration and diversity, which was the first investigation of the role of social capital in a particular policy area- Catherine and Jean took the lead on that initiative. Sylvain Côté contributed to this collaborative effort from the OECD. Jeff Frank was project director throughout this phase of activity. When he went on parental leave in Spring 2004, Catherine Demers was project director from April 2004 to March 2005, and oversaw project activities in developing the thematic policy studies. Jeff rejoined the team in the spring of 2005, coordinating the finalization and dissemination of the project products.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.027 | 0.010 |
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; both teacher heads agree on what is shown here.
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".