Dehumanization in organizational settings: some scientific and ethical considerations
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
Dehumanizing attitudes and behaviors frequently occur in organizational settings and are often viewed as an acceptable, and even necessary, strategy for pursuing personal and organizational goals. Here I examine a number of commonly held beliefs about dehumanization and argue that there is relatively little support for them in light of the evidence emerging from social psychological and neuroscientific research. Contrary to the commonly held belief that everyday forms of dehumanization are innocent and inconsequential, the evidence shows profoundly negative consequences for both victims and perpetrators. As well, the belief that suppressing empathy automatically leads to improved problem solving is not supported by the evidence. The more general belief that empathy interferes with problem solving receives partial support, but only in the case of mechanistic problem solving. Overall, I question the usefulness of dehumanization in organizational settings and argue that it can be replaced by superior strategies that are ethically more acceptable and do not entail the severely negative consequences associated with dehumanization.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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