Building a Policy Muscle: Learning from Northern Youth about Arctic Tourism
Bibliographic record
Abstract
The Northern Review 57: 171–177 Sharing the Arctic: A Sustainable Future for Arctic Tourismhttps://gordonfoundation.ca/resource/2024-arctic-policy-hackathon-policy-recommendations/Abstract: This article reflects on policy recommendations from the third Arctic Policy Hackathon, the importance of cross-Arctic collaboration, and why young leaders from the Canadian North should engage with policy development. Policy Hackathons see young leaders from diverse backgrounds collaborate on a significant policy issue, in this case how to keep the next generation of leaders in the Arctic. It is a model of learning about policy that prioritizes the voices and lived experience of the next generation of leaders, brings their ideas to the forefront, and gives them the skills to turn ideas into action. The third Arctic Policy Hackathon, organized by the Gordon Foundation in partnership with the Arctic Mayors’ Forum and with support from Global Affairs Canada, saw emerging leaders from the Canadian North join their counterparts from across the Arctic in Reykjavik, Iceland. Participants also engaged with policy leaders and shared their recommendations at the Arctic Circle Assembly, taking valuable lessons back to their home communities. Résumé: Cet article présente les recommandations politiques issues du troisième Hackathon politique pour l’Arctique, souligne l’importance de la collaboration circumpolaire, et explique pourquoi les jeunes leaders du Nord canadien devraient s’impliquer dans l’élaboration des politiques. Les Hackathons politiques réunissent de jeunes leaders de divers horizons pour collaborer sur une question politique majeure, ici comment assurer la relève des leaders en Arctique. Ce modèle d’apprentissage politique met en avant les voix et l’expérience vécue de la nouvelle génération, valorise leurs idées et leur donne les outils pour les transformer en actions concrètes. Le troisième Hackathon politique pour l’Arctique, organisé par la Gordon Foundation en partenariat avec l’Arctic Mayors’ Forum et avec le soutien d’Affaires mondiales Canada, a rassemblé des leaders émergents du Nord canadien avec leurs homologues de tout l’Arctique à Reykjavik, en Islande. Les participants ont aussi échangé avec des décideurs politiques et partagé leurs recommandations lors de l’Assemblée du Cercle Arctique, ramenant des leçons précieuses dans leurs communautés. French translation, Sara Tahiri
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".