Bibliographic record
Abstract
As First Nation economies begin to take shape and grow across the country, efforts turn from start-up to sustainability.Ensuring that economies grow and are sustainable over the long term becomes an important undertaking requiring institutional development, public policy support, and the fostering of a set of attitudes and values that blend both economic and Indigenous Knowledges.This issue of JAED explores several aspects of sustainable economic development: Thompson, Gulnruk, Beardy, Islam, Lozeznik and Wong examine food sovereignty in Northern Manitoba; and Connelly, Markey and Roseland examine sustainable community planning at the Rolling River First Nation in Manitoba.Findlay and Weir examine aspects of development using the lens of Indigenous Knowledge (IK), proposing that a new accounting model that places IK at its centre will contribute to improved Aboriginal sustainable practices.Natcher, Allen and Schmid examine the low (3% vs. 80% for non-First Nation producers) participation of First Nations cattle producers in government financial aid programs during the 2003 Bovine Spongiform Encephalopathy (Mad Cow Disease) crisis.Bullock highlights the importance and value of First Nation and Municipal Government collaboration using a case of forest-based development, and finally Berdahl, Beatty and Poelzer examine the critical, indeed required, associations with women and youth when addressing Aboriginal community development in Canada.
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 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 | 0.003 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.177 | 0.084 |
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".