Envisioning Global LGBT Human Rights: Strategic Alliances to Advance Knowledge and Social Change
Bibliographic record
Abstract
The Envisioning Global LGBT Human Rights research project involves working collaboratively with community partners, both local and international. This article presents the research currently being conducted and some of the challenges in undertaking knowledge engagement between academia and the community with the project’s Canadian, African, and Caribbean partners by means of participatory action research (PAR). Specifically, the article gives examples of the project’s work and explores the following topics: work with Global South partners and marginalized communities; strategic alliances; knowledge production and mobilization; and methodologies that have contributed to successes or challenges. Knowledge engagement at the international level, with its variances in resources, power, and autonomy, increases the demands of such work and the need for sensitivity in reaching the goals of the project and those of all of its stakeholders.Résumé: Le projet Envisioning Global LGBT Human Rights implique le travaille en collaboration avec des partenaires communautaires, à la fois locaux et internationaux. Cet article présente les recherches actuellement menées et des défis à entreprendre l’engagement de connaissances entre le milieu universitaire et nos partenaires communautaires canadiens, africains et des Caraïbes. Le document donne des exemples de notre travail et explore les thèmes suivants : travailler avec les partenaires du Sud planétaire et les communautés marginalisées; les alliances stratégiques; la production de connaissances et son mobilisation; les défis de la recherche participative; ainsi que des méthodologies qui ont contribué à nos succès ou défis. L’engagement de connaissances au niveau international avec des écarts en matière de ressources, de pouvoir et d’autonomie contribue aux défis d’un tel travail et le besoin de sensibilité pour atteindre les objectifs du projet et l’ensemble de ses parties prenantes.
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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 | 0.037 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.016 | 0.048 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.002 | 0.033 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".