An evaluation of Aboriginal, government, and mining industry relationships and policies in Manitoba: Accessing land for mineral exploration and mine development
Bibliographic record
Abstract
The thesis focused on evaluating how provincial policies have framed and informed the development of relationships among Aboriginal, government and mining industry representatives in Manitoba. The research was conducted during a time period where current events regarding uncertainties in land claims, delays in obtaining prospecting work permits and a need for clarifying Section 35 Crown consultation have amplified the need for further understanding of the interactions among the parties. The research adopted a qualitative approach that consisted of a literature review, key-informant interviews and general observations. Thirty interviews were conducted from August to November 2014. The results revealed that the existing relationships among the parties were frustrating. These frustrations were attributed to a breakdown in the implementation and application of provincial policies and procedures. Uncertainties in land claims and protected area designation have continued to deter investment into the mineral sector. A lack of communication, understanding of cultural backgrounds, and willingness to allow time for proper consultation was noted by the respondents. Failure to recognize these aspects within policy has taken a toll on enhancing lasting relationships. Policies need to be updated and should clarify the roles and responsibilities of each interested party.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".