Gender, participation, and environmental decision-making: Case study of the proposed Jumbo Glacier Resort
Bibliographic record
Abstract
This study focused on understanding the role of gender in people’s participation in the proposed Jumbo Glacier Resort decision-making processes in southeastern British Columbia, Canada. Research questions focused on the ability of Transgender people, women, and men to participate meaningfully, and the identification of enabling and constraining factors of participation. Respondents had experience with formal and/or informal decision-making processes regarding the proposed Jumbo Glacier Resort. Qualitative methodology was used to gather data through interviews, surveys, site research, and archival sources, which were analyzed using thematic content analysis. According to most respondents, gender impacted people’s participation in the proposed Jumbo Glacier Resort decision-making processes by determining whether they held the right “key” to access participation; which respondents determined was held by men. \nConsequently, these findings show that the proposed Jumbo Glacier Resort decision-making processes were gendered, and were not representative of everyone who was impacted by the decisions. In 2017 this type of exclusion is no longer appropriate, and as both the literature and numerous international agreements point to, in order to achieve human sustainability, we all need to work together.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".