Commentary on Loughrey M (2008) Just how male are male nurses..? <i>Journal of Clinical Nursing</i> 17, 1327–1334
Bibliographic record
Abstract
The enduring mystery of gendered occupations and the place of those in the minority gender drew me to this paper. Also, the fact that I am a man in nursing heightens my sensitivity to the issue. Note, I describe myself as a ‘man in nursing’ and not as a ‘male nurse’– the description used by Loughrey (2008). My experience in nursing began as an auxiliary in learning difficulties (then called mental handicap!) where several male members of my family worked and where a great many men worked and the issue of gender in nursing was never an issue for me, although I realised that men in general nursing were in the minority. When I began my training our tutor – a man, as a great many in education were – said that we should not use the expression ‘male nurse’ as there was no with thing; there were only nurses and men in nursing. Therefore, this has stuck with me but is not a criticism of Loughrey – men in nursing are, indeed, male nurses. Nevertheless, men in nursing remain vastly in the minority, until you move into management and education, but that is separate issue. Being in the minority makes us unusual, indeed ‘abnormal’ in statistical terms where approximately 90% of nurses in the UK are female. Until very recently it was illegal, for example, in Turkey to be a man in nursing and I visit one private hospital in the North of Spain where – under the influence of some misguided people – male nurses are also absent. So, what is the issue with men in nursing? There are other professions, primary school teaching for example, where men are vastly in the minority – except, again, as head teachers. As a father of eight children with whom I have moved around the UK we have experienced four primary schools and encountered four male teachers, three of whom were the head teacher. However, this does not seem to be an issue – unless I have missed something. In particular, the sexuality of these men in primary teaching is not raised and does not elicit the reactions that men in nursing sometimes do. Therefore, the issue of men in nursing remains interesting in itself and also in relation to the nursing workforce. The nursing workforce is ageing worldwide (Andrews et al. 2006) and men in nursing are disproportionately represented, as Loughrey points out, in disciplinary proceedings. Loughrey’s study demonstrates, using a sex role inventory, that men in nursing adhere more to female gender roles than to male gender roles. This reflects findings from one of my own studies (Watson & Lea 1998) which showed that men, unexpectedly, perceive caring more in psychosocial terms than in technical terms which is counterintuitive to people who think that men in nursing are there due to their liking for gadgets and tinkering with medical equipment. Therefore, it appears that men in nursing are different from men who are not in nursing. These findings, to some extent, reinforce stereotypes, but also provide useful information about men in nursing and may have the potential to be exploited in recruiting and retaining men in nursing. It contrasts nicely with a North American poster I picked up at a conference in Canada which showed a series of men in military uniforms, in hunting and shooting gear and, generally, looking ‘macho’– presumably this was designed to overcome stereotypes about men in nursing; frankly, I thought it was a joke. Likewise, one of the largest studies of men in nursing carried out at the University of Hull (Brown & Stones 1973) showed some significant differences between men and women in nursing on the basis of personality. Using Eysenck’s Personality Inventory it appeared that men in nursing were more likely to be liars than women – not a god advert for our place in the profession. I hope that Loughrey’s study will be read and that this strand of work will continue. The place of men in nursing is not seriously questioned these days and if we’re different –vive la difference!
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.052 | 0.070 |
| Insufficient payload (model declined to judge) | 0.014 | 0.014 |
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".