Two-Spirits’ response to COVID-19: Survey Findings in Atlantic Canada identify Priorities and Developing Practices
Bibliographic record
Abstract
The Wabanaki Two-Spirit Alliance (W2SA), a regional Two-Spirit organization, administered an online survey in May of 2020 to identify priorities and concerns of Two-Spirit (2S) individuals and Indigenous 2SLGBTQQIA+ people in Atlantic Canada during the novel coronavirus (COVID-19) pandemic. The respondents (n=149) shared health concerns including deterioration(s) of mental health (56.32%) and described mental health supports (68.42%), health supports for Two-Spirit individuals (57.89%), healing gatherings (46.05%) and trans-specific supports (44.74%) as critical interventions in fostering Two-Spirit health. The Alliance’s immediate response was to develop community-led responses to address urgent concerns. Our key promising practice has been hosting Two-Spirit gatherings as community-based health/cultural supports; the gatherings also serve as an opportunity for the Alliance to consult the Two-Spirit community about priorities and concerns. During the COVID-19 pandemic, the Alliance explored ways to keep the Two-Spirit community safe while maintaining critical social support(s) and gaining invaluable knowledge from the Two-Spirit community. We designed a survey that provided critical feedback resulting in the Alliance shifting priorities towards developing ways to bring Two-Spirit people together safely by virtual means, seeking sustainable resources to address emerging health concerns, and increasing capacity development of the Alliance.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".