Methodological Diversity: Community-driven Development of a Digital Library for Northern Communities
Bibliographic record
Abstract
The objective of this paper is to report on a community-driven methodological framework developed for the exploration and development of a digital library for northern communities. More specifically, this paper addresses methodological approaches and techniques for studying the communities in the Inuvialuit Settlement Region in Canada’s north. L'objectif de cet article est de faire rapport sur un cadre méthodologique axé sur la communauté développé pour l'exploration et le développement d'une bibliothèque numérique pour les collectivités du Nord. Plus précisément, ce document aborde les approches méthodologiques et techniques pour l'étude des communautés de la région désignée des Inuvialuit dans le nord du Canada.
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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 | 0.089 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.019 | 0.015 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".