Development of a Digital Library Infrastructure for the North: An Environmental Scanning Approach
Bibliographic record
Abstract
This paper reports on an ongoing project: thedevelopment of an environmental scanning model asa basis for the creation of a digital libraryinfrastructure for the Inuvialuit Settlement Region inCanada’s north. The model is proposed as a novelapproach to community-focused digital librarydevelopment and the paper also presents keyemerging findings from the use of environmental scanmodel.Cette étude rend compte d’un projet en cours : ledéveloppement d’un modèle d’analyse del’environnement comme base pour la création d’uneinfrastructure de bibliothèque numérique destinée àla région d’établissement Inuvialuit dans le Nordcanadien. Le modèle est proposé comme unenouvelle approche pour le développement d’unebibliothèque numérique axé sur la communauté etl’étude présente également les principaux résultatsissus de l’utilisation du modèle d’analyse del’environnement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".