Ethical perspectives of library and information science graduate students in the United States
Bibliographic record
Abstract
Purpose The purpose of this study was to examine the ethical perspectives of library and information science professionals prior to their entry into the profession. Design/methodology/approach The population consisted of 46 graduate students enrolled in a library and information science program during summer 2003. Three scenarios related to general, legal, and health ethical issues were used. Participants were randomly assigned to a scenario. First, they read the scenario and provided initial reactions. Second, they read the professional code of ethics related to the scenario. Finally, they re‐read the scenario and provided reactions based on the professional code of ethics. Findings The initial reactions of participants to the scenarios were similar to their reactions after reading and applying the assigned code of ethics. For example, participants initially reported that the library director should permit staff to attend the American Library Association conference in Toronto even with the SARS issue (85 percent), After reading the Health Sciences Code of Ethics, they selected promoting access to health information and working without prejudice to support their positions. Originality/value The findings of this study illustrate the influence of codes of ethics on students' ethical perspectives. Investigating the professional ethics of future library and information science graduate students is of value to students and faculty.
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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 | 0.016 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.013 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| 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".