Reply: Eslamialiabadi H, Nasiri A, Mahmoudirad G. Iranian Men’s Sexual Life Issues After Their Wives’ Burn: A Qualitative Content Analysis Study. J Burn Care Res 2023;44(2):452–458
Bibliographic record
Abstract
To The Editor, The spouse or intimate partner of a burn survivor may secondarily experience sexual difficulties and reduced quality of life. Although Eslamialiabadi’s study1 identifies the important but under-discussed secondary effect of burn injury on the uninjured intimate partner’s sexuality, we have several concerns. First, only the perspectives of uninjured male spouses of female burn survivors were considered. To appreciate sexuality and sexual satisfaction of people in a committed relationship, the experience of both partners needs to be heard.2 The study could have collected and reported qualitative data from uninjured female partners of male burn survivors, or those of the female burn survivors. Ideally, a dyadic approach, considering the injured and uninjured as a couple, could have been employed.3 Second, while direct quotes of participants are relevant to this type of qualitative research, there are pejorative terms and expressions used throughout the article. Despite cultural differences in sexuality, without the perspective of the wives represented, we find many terms troubling and believe that this information should have been conveyed in a less biased fashion. Many readers would find the article difficult and not equitable. This is unexpected from an article in a scientific journal, which is a forum for the worldwide burn community.
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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 | 0.006 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.025 | 0.038 |
| Insufficient payload (model declined to judge) | 0.020 | 0.016 |
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".