Public Library is….; Mapping Stakeholder Perspectives on the Values and Purposes of the Public Library
Bibliographic record
Abstract
We used survey responses and statements of library organizations to create a corpus of items describing the value of public libraries. A sample of public library users and staff from the province of Ontario individually sorted these statements into groups and labelled the groups, and rated each statement with respect to its general importance, its centrality to the mission of the public library, and its uniqueness to the public library. We used GroupWisdom™ software to analyze individual responses into an overall concept map and to identify differences in patterns across different participant groups. Nous avons utilisé les réponses aux sondages et les déclarations des organisations de bibliothèques pour créer un corpus d'articles décrivant les valeurs des bibliothèques publiques. Un échantillon d'utilisateurs et d'employés des bibliothèques publiques de la province de l'Ontario a trié individuellement ces énoncés en groupes et étiqueté les groupes, et a évalué chaque énoncé en fonction de son importance générale, de son rôle central dans la mission de la bibliothèque publique et de son caractère unique pour le bibliotheque publique. Nous avons utilisé le logiciel GroupWisdom ™ pour analyser les réponses individuelles dans une carte conceptuelle globale et pour identifier les différences dans les modèles entre les différents groupes de participants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".