Bibliographic record
Abstract
Folkebiblioteker i Danmark har siden 2000 set sig, hvad biblioteksbetjeningen af etniske minoriteter angår, som et frirum til integration. Frirum-metaforen har givet bibliotekernes erfaringer retning og legitimitet. Artiklen spørger, om frirum-metaforen i 2015 stadig er en passende respons på de etniske udfordringer. Spørgsmål søges besvaret ved at spejle danske erfaringer i canadiske. Hvordan har det canadiske biblioteksvæsen reageret på den øgede tilflytning af etniske minoriteter? Hvilken samlende metafor har bibliotekerne i Canada skabt? Et svar på disse spørgsmål bruges til at se nærmere på de muligheder og begrænsninger, der knytter sig til frirum-metaforen og at få et mere nuanceret billede af den multikulturelle udfordring. Artiklen udgives i to dele.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".