Bibliographic record
Abstract
Objective: We believe there are ethical issues that emerge in the management of hospital health units, therefore in this article we discuss the interface between the areas of Bioethics and Management. This research aims to contribute to the operationalization of a profile of ethical competencies to manage hospitals with ethical weighing and linkage to values.Methods: This is an exploratory and descriptive study with 421 hospital managers of 25 hospitals in the northern zone of Portugal, integrated in the National Health Service. To collect data, we used the Questionnaire of Ethicity in Hospital Management and analyzed the contents of the electronic pages of 36 hospitals about the mission, values and vision they advocate.Results: In addition to the philosophical perspective of each person, health professionals in hospital management respect the complex multidimensionality, recognizing the singularity and the personal, social and cultural individuality. Values and personal ethics can be a guide for action in the field of health. In the results of this study, we present a framework of ethical competencies for the management of the hospital, which aims to optimize management with ethical weighing with the following dimensions: Decision, Primacy of the human person, Responsibility, Integrity, Training and development, Equity and access, Organization and Social Responsibility.Conclusions: Based on the results of this study, we conclude that there is a need to implement a matrix of ethical competencies that guide health professionals to respect people and their rights – in the management of health care and services, in clinical practice or in scientific investigation. The managers of the hospitals integrate the guidelines in the code of ethics of their professional group and in the mission, values and institutional vision. Overall, they claim to have a framework of ethical competencies, acting with reference to the ethical paradigm of personalism.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".