The Civil Justice System and the Public Justice for Nunavummiut: Partnerships for solutions
Bibliographic record
Abstract
As part of the Civil Justice System and the Public (CJSP), a national collaborative research project, we first visited Iqaluit in June 2003. At that time the Research Coordinator met with key contacts in the Nunavut justice and social service community to talk about the research and make plans for conducting the field research. As a result of these initial meetings, the CJSP team made contact with Inuit services in Ottawa. In July 2003, during the Ontario phase of the CJSP research, we met Inuit service providers and several Nunavummiut who were at that time living in Ottawa.1 In September 2003, the CJSP Research Team came to Iqaluit and over a period of two weeks completed 28 in-depth interviews. Eighteen people (eleven women and seven men) worked within the justice community and included members of the judiciary as well as court administration and frontline staff. We also interviewed ten members of the public (two women and eight men) who were either personally involved in court cases at varying stages of resolution, or acting as community advocates to people with legal problems. In order to increase the team’s understanding of Nunavut, researchers also compiled observation notes and held many informal conversations with Iqaluit residents as well as key contacts in some other Nunavut communities.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.045 | 0.026 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 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".