Causing harm but doing good: Recognizing and overcoming the burden of necessary evil enactment in healthcare service professions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Necessary evils - defined as acts that cause physical, psychological, or emotional harm to victims but are for the greater good of either the victim or society - are an everyday occurrence in the healthcare industry across the globe and across healthcare service professions. Healthcare professionals are tasked with behaviors that result in pain and suffering (e.g. nurses providing shots to patients; oncologists communicating cancer diagnoses) for the betterment of their patients and stakeholders. Although these behaviors are professionally mandated, they can also be cognitively and psychologically taxing for enactors. The current conceptual paper explores the undesired effects of performing necessary evils and proposes various actions through which healthcare organizations can reduce the negative repercussions of necessary evil enactment on healthcare service professionals.
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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 | 0.031 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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 it