Gender Differences in Making Moral Decisions: The Ethics of Care Perspective in Pakistan
Bibliographic record
Abstract
This research explored how an ethics of care is practised in a communitarian society in Karachi, Pakistan. To this end 24 participants were interviewed, 12 males and 12 females aged between 19 and 32 years. We used a culturally adapted version of The Ethics of Care Interview (ECI). This adapted measure focused on lived experiences of participants resulting in an Interpretative Phenomenological Analysis (IPA) of interview transcripts to explore ethics of care among study participants. The themes that emerged during IPA included the negotiation between norms related to religion and culture, familism, and gender differences. These analyses confirm the link between gender and the ethics of care indicating that women share higher concerns for care, often demonstrating empathy and sacrifice. The results also show that men expect women to care for others and behave in self-sacrificial ways. The intersectional nature of our study shows that culture and not gender may ultimately explain the ethical considerations of men and women. This means that both men and women justified their ethical choices of care because they believed they had a responsibility to do so. This shows that care ethics are more strongly dictated by societal norms of collectivism.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".