CBERN-NNK Knowledge Needs Research Summary:Report to the CBERN/Naskapi Steering Committee and the Naskapi Community
Bibliographic record
Abstract
This report has been prepared for the Naskapi Steering Committee and the Naskapi community by Peter Siebenmorgen Research Assistantand Dr. Wesley Cragg, Project Director. The Canadian Business Ethics Research Network (CBERN) has been working in collaboration with the Naskapi Nation of Kawawachikamach (NNK) since early 2007. This relationship was initiated by former NNK Chief Phil Einish. The goal has been to ensure that the Naskapi people benefitted from mining on their traditional territories and avoided the negative impacts caused by previous mining activity by the Iron Ore Company of Canada. Working with Naskapi leadership, Dr. Cragg and Dr. Bradshaw developed a plan to identify community concerns and hopes for mining development on their traditional territory and provide access to the information and knowledge the community needed to address those concerns and hopes. The goal is to provide the community with the information it requires to benefit from development now taking place.The first step in the plan has now been completed. This report to the Naskapi community describes what the research team found.The second part of the plan is to improve access to information that will help the community address its concerns and realize its hopes for building a better and stronger future.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".