Authentic and ethical leadership during a crisis
Bibliographic record
Abstract
In today's climate and environment, the conventional relationship between caring, economic, and leadership practices may no longer meet the needs of patients, clinicians, providers, or systems. It is asserted that in the current complicated and complex healthcare environment challenged by a multitude of issues, a shift toward human caring values and an ethic of authentic healing relationships is required, especially in light of the current COVID-19 pandemic. The costs of unethical behaviour can be even greater for followers. When we assume the benefits of leadership, we also assume ethical burdens. It is the assertion and experience of the authors that the triangle of ethics and ethical behaviour, followers, and patient outcomes is closely interrelated and affects each other in a very intimate and direct way. Unethical leadership may lead to follower disappointment and distrust, leading to lack of interest and commitment, consequently negatively impacting patient outcomes and organizational effectiveness.
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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".