Intertribal Timber Council survey of tribal research needs
Bibliographic record
Abstract
This paper presents the results of the first systematic attempt to understand the research needs, priorities, and interests of Native American tribes’ forest resource managers and decision-makers. In 2011 the Intertribal Timber Council disseminated a survey to 129 individuals that represented over 30 tribes as well as a variety of federal agencies and research/education institutions. The survey sought to evaluate the relative importance of a variety of research topic areas as well as better understand impediments to research faced by the tribes and evaluate the relative attractiveness of different opportunities for collaborations and partnerships. Results from the survey reveal three important themes: 1) tribes place particular importance on research related to water, fisheries and other “non-timber” values; 2) collaboration and cooperation are very important, especially concerning (but by no means limited to) the integration of traditional knowledge with western science; and 3) adaptation of research to the local landscape is of greater value than pursuing peer-reviewed, original research for its own sake. The findings of this survey will provide an important tool to the new ITC research subcommittee as it attempts to aid in the creation of culturally responsive, tribally driven forest-based research.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".