Ecological research should consider Indigenous peoples and stewardship
Bibliographic record
Abstract
The relationship between Indigenous peoples and the functioning of terrestrial ecosystems has received increased attention in recent years. As a result, it is becoming more critical for researchers focusing on terrestrial ecosystems to work with Indigenous groups to gain a better understanding of how past and current stewardship of these lands may influence results. As a case study to explore these ideas, we systematically reviewed articles from 2008 to 2018 where research was conducted in North America, South America, and Oceania. Of the 159 articles included, 11 included acknowledgement of Indigenous stewardship, acknowledged the Indigenous Territories or lands, or named the Indigenous group on whose Territory the research was conducted. Within the scope of this case study, our results demonstrate an overall lack of Indigenous acknowledgement or consideration within the scope of our review. Given the recent advancements in our understanding of how Indigenous groups have shaped their lands, we implore researchers to consider collaboration among local Indigenous groups as to better cultivate relationships and foster a greater understanding of their ecosystems.
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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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".