GENDER AND DECISION-MAKING IN NATURAL RESOURCE CO-MANAGEMENT IN YUKON TERRITORY
Bibliographic record
Abstract
Across the Canadian North, resource co-management has become a central institution for the management of natural resources. An inventory of co-management boards in Canada’s northern territories, conducted in 2012, identified more than 30 different boards, with responsibilities ranging from wildlife, water, lands and non-renewable natural resources (Natcher 2013). While operating along a continuum of institutional authority, co-management has been heralded by many as an effective means to engage resource users and government managers in a collaborative and more equitable approach to environmental decision-making. Although a considerable amount of multi-disciplinary research has examined the various social and political dimensions that influence the effectiveness of resource co-management, little has been done to understand how gender might affect collaboration and decision-making within this resource regime. This gap in understanding is particularly evident in the northern Canadian context, where women make up 16% of all current co-management board members. With the intention to address this analytical void, this study set out to examine the ways in which a gender imbalance influences board decision-making and the experiences of those involved in co-management boards that have been established in the Yukon Territory. It focused in particular on women within these institutions, while also acknowledging broader gender roles that involve both men and women. Written surveys and semi-structured interviews demonstrated that the representation of women within these institutions was important to establishing a holistic decision-making process and positive institutional culture that facilitated effective decision-making. The presence of women on these boards also influenced the scope and efficacy of decision outcomes. Participants found that though opportunities to participate in decision-making existed, there were still barriers preventing board members from acting on these opportunities. These barriers were often experienced by men and women in different ways. Implicit within these findings are the gendered roles and characteristics that shape the activities and expectations of those involved with co-management institutions. Gendered roles in the community and on the land were particularly relevant to these boards. This research contributes to a more informed understanding of a critical, yet unexplored, aspect of the social and political context of co-management, with practical implications for how effective decision-making is interpreted and implemented by these boards.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".