Developing An Economic Partnership Framework Between The Lheidli T'enneh First Nation And Initiatives Prince George Development Corporation
Bibliographic record
Abstract
Both non-aboriginal corporations and First Nation bands are recognizing the benefits of forming economic partnerships. Each First Nation is unique and economic partnerships have to be designed to fit the partners capabilities. The purpose of this paper is to discuss the development of a framework for an economic partnership between the Lheidli Tenneh First Nation and the Initiatives Prince George Development Corporation. This framework was intended to offer structure, engagement, and guidance to that partnership. The economic development framework was created by a committee composed of representatives from the two parties with one of the authors acting as the facilitator. The committee identified nine elements that were deemed important to their relationship. It expanded on each of these elements under the headings of our definition, strategic actions and performance measures. The framework developed by the committee is intended for the Lheidli Tenneh First Nation and the Initiatives Prince George Development Corporation but can serve as a guide for other parties.
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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 | 0.032 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".