Bibliographic record
Abstract
This section describes the strategies and motivations of those addressing the challenges and conflicting views regarding resource development.Meet Mark Sark, CEO of Gespe'Gewaq Mi'gmaq Resource Council, "the best natural resource and environmental organization in eastern Canada."You are invited to find out why he says this and learn about significant influences brought to bear on his work.Gaming is a growing industry and Enoch Cree Nation has been a leader that is willing to share experiences fully in their challenging journey to realize community goals.Paulette Flamond brings 15 years of entrepreneurial experience to her current position with the Aboriginal Business Service Network Society.She has a strong focus with a number of organizations and projects on Aboriginal economic development.Many communities are facing natural resource development opportunities.They must deal with companies and contracts that will impact the futures of their ways of life.Based on research in and around Baker Lake, Nunavut, Warren Bernauer examines the consulting phase of this process in detail.He questions current consultative processes and makes recommendations for nurturing a stronger community role.Finally, individual training needs are recognized in an article by Robert Oppenheimer, Tom O'Connell, and Warren Weir.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.001 | 0.000 |
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".