Bibliographic record
Abstract
Purpose There are numerous professional associations for librarians and libraries. A small proportion of these have promulgated codes of ethics. These codes of ethics vary along several dimensions. Often the code reflects the social, political, or professional mandate of its organization. This paper aims to address ethics codes and their functions in professional associations that have individuals as members. Design/methodology/approach It is suggested that for these organizations there are several different types of ethics codes. This paper addresses the four most common types. The oldest code (American Library Association), one of the newest (Association des Bibliothécaires Français), and two of a more average age (Canadian Library Association and Colegio de Bibliotecarios de Chile) are compared and considered in detail. Findings The paper finds that, while most library and information professionals share similar values, as reflected in their codes of ethics, the application of those codes varies widely. Originality/value The paper provides useful information on codes of ethics for libraries and librarians.
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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 | 0.031 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".