Proyecciones estratégicas en bibliotecas públicas: ¿qué, cómo y para qué?
Bibliographic record
Abstract
Public libraries contribute to free and open access to information, promote inclusion and social cohesion in an info‐diverse and multicultural space, stimulate lifelong learning, encourage citizen participation, and support empowerment and development of communities. Public libraries guide these actions in accordance with the goals and objectives that make up their strategies and projections. Public library performance in Canada, Chile, Colombia, Croatia, Denmark, Slovenia, Spain, the United States, Hong Kong, England, Lithuania, Norway, Poland and the United Kingdom are examined. In addition, the strategic projections of public libraries are analyzed in some of these contexts, and the convergence between its functions, goals, objectives and actions that they pursue for the benefit of the communities are noticed. Those goals are achieved, from the documental and content analysis of the strategic documents and the scientific production related to the actions of these public libraries.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.032 | 0.020 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".