A typology of Inuit youth engagement in environmental research
Bibliographic record
Abstract
The roles of Indigenous youth in environmental research remain largely unexplored with little practical guidance for achieving meaningful engagement in environmental research. This paper aims to characterize the varying types of Inuit youth engagement in environmental research conducted in Inuit Nunangat. Findings were derived from a community-engaged participatory research approach in Mittimatalik (Pond Inlet, Nunavut). Our typology of Inuit youth engagement in environmental research suggests three types of engagements: “participate”, “conduct”, and “control”. Results highlight that Inuit youth who are interested in undertaking their own environmental research projects expect to enhance their knowledge of natural and life sciences more than those who may seek short-term supportive research roles. Strategies employed by researchers seeking to enhance youth research capacity may also vary based on youth wants and expectations. Our findings suggest that there is no one-size-fits all solution. None of the engagement types identified were necessarily and inherently considered better than the others by project contributors, unlike what has been proposed in other, hierarchical, typologies. Our proposed typology contributes to a better understanding of the varying roles that Inuit youth can play in environmental research, as well as inform potential frameworks for enhancing Inuit youth engagement and leadership in 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".