The need for global certification in the field of health informatics: some ethical issues.
Bibliographic record
Abstract
In the past, the training of health information professionals (HIPs) has focussed almost exclusively on technical matters, the concerns of software developers and purveyors have essentially centred on security and functionality, and health care providers have mainly worried about costs and efficiency. This paper outlines some ethical threats that are ignored by such a purely technical focus and argues that because of the increasing globalization of health care delivery through e-Health, and because of the international threats to confidentiality posed by legislation such as the US Patriot Act, the health informatics community should pursue a project of global certification for HIPs that includes information ethics as an integral component. It also argues that a corresponding certification process for health care institutions and software developers should be initiated.
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 | 0.091 | 0.089 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.036 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.019 | 0.024 |
| Insufficient payload (model declined to judge) | 0.002 | 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".