Bibliographic record
Abstract
Medicine has changed a lot since the turn of the most recent century; it's now been 22 years since the clocks ticked over into the ‘future’ that was the near horizon for the Australian television show, Beyond 2000. I entered medical school in 1997 feeling utterly alone and without representation; I'd come from a single-parent family and attended a public school – only four graduates went to university. I was also mixed race and gay. It was not uncommon in the 1990s to hear of gay men being refused hospital entry to visit a partner because the rules dictated ‘family only’ and did not recognise same-sex relationships. Australia only recognised my marriage certificate in 2017, 3 years after I got married in Canada. I had not intended to be a doctor. I hated going to the doctor because they made you wait, without apology, and made wrong assumptions. I didn't trust doctors, and I didn't like to hear of people like me being excluded from hospitals because of who they loved. With my teenage reasoning, the only solution was to become a doctor myself and re-write hospital rules. This special issue of JMIRO is the second in a series that examines diversity, equity and inclusion: in our colleagues, our patients and ourselves. This issue examines gender diversity, specifically representation of women authored by women, acknowledging that there is a void of data regarding the presence, contributions and workplace experiences of gender non-binary and transgender providers. It also offers our readership personal and institutional tactics on how to fully include sexual and gender minorities. Future special issues will address racial and cultural diversity, as well as hearing from Aboriginal and First Nations voices from Australia and New Zealand Aotearoa. Disability inclusions are not yet planned but are also important. Central to these special issues is listening to those with lived experience and taking direction from them. The health inequalities and inequities experienced by our patients and the workplace inequalities experienced by healthcare providers are a by-product of the common culture in which we live. Solutions to both sets of problems are intersectional.1 We all have a role. To date, RANZCR has only collected fellows' gender data as a binary categorical variable. This issue's papers on gender diversity highlight the under-representation of women in radiology. Moriarty et al. report on gender imbalance in interventional radiology; Yap et al. report on radiation oncology gender pay gap; Lim et al. examine gender in workforce planning; Hayter and Ayesa report on female representation in subspeciality interest groups; Batumalai et al. report on assumed gender trends in first and senior authors in JMIRO publications; Hesselberg et al. report on gender diversity and leadership in radiation oncology. Georgousakis provides an account on mentoring for women. Sexual minorities are often lumped together in broad-brush approaches that use increasingly long acronyms that are as much a word salad for readers as the diversity of people that they conglomerate. For example, attempts to include nonheterosexual human sexual identities can be made maximally inclusive but unworkably complex by the acronym ‘LGBTQQIP2SAA+’ (Lesbian, Gay, Bisexual, Transgender, Questioning, Queer, Intersex, Pansexual, Two-Spirit, Androgynous, Asexual +).3 The two articles in this special issue addressing diversity of sexuality have chosen to report on LGBTQIA+ people: Bird et al. offer suggestions for individuals and institutions on workplace inclusivity; Chapman et al. report on a qualitative study on gaps in knowledge for radiologists and radiation oncologists in caring for LGBTQIA+ patients. RACS and RANZCOG are both ahead of RANZCR in policies and actions around diversity, inclusion, and equity and the paucity of invited submissions for a special issue on diversity reflects this. However, RANZCR has now literally joined the march forward with the Board's endorsement to participate in a combined medical speciality college entry in the Sydney World Pride 2023 Mardi Gras Parade, organised by the bi-national network of specialists and medical students, Pride in Medicine. How is JMIRO changing in the context of these special issues? The Medical Journal of Australia has reported on gender inequity for women in medicine4 and now recommends that authors of research published in the MJA follow the Sex and Gender Equity in Research (SAGER) guidelines.5 The American Journal of Radiology has made recommendations for more inclusive language in figure legends and gender descriptors.6 It would seem an easy solution to simply adopt any suggested inclusive language alternative. But, using new blanket terminology without context, consultation or consent, can quickly backfire, especially if people perceive erasure. Women were dehumanised when the Lancet Sep 2021 cover Tweet quoted ‘bodies with vaginas’ without context, and the cover Tweet went viral. My skin crawls when reading research papers about people like me, referred to as ‘CaLD’ (culturally and linguistically diverse, but pronounced ‘cold’) or ‘MSM’ (men who have sex with men, not mainstream media); I didn't choose these names. In studies including only participants who have had the opportunity to confirm that they identify as women, then female-gendered language terms recognising womanhood are expected. Assumptions on participant gender are, however, exclusionary and result in identity erasure. There is no easy solution or shortcut from asking the right questions at the right time. Attempts at change may get shot down immediately because of imperfection; it's easy to reject any solution that doesn't immediately solve all problems. It is also easy to speak over and alienate a group of people, if advocating without their engagement or consent. Whop et al.7 describe this concept well in ‘The Blackfulla test’ for active representation in Indigenous health research. Every member of RANZCR, our colleagues, and our patients all deserve respect, to be counted, and to have a voice. We need to be precise and correct in our data collection and reporting, as we work towards optimising health outcomes. We earn our patients' trust by respecting their autonomy and this includes affirming their identity and who will visit them in hospital. The assurance of being able to visit a hospitalised same-sex spouse shouldn't be limited to those who have attained the privilege and authority of a medical degree. However, those who do possess the privilege and authority inherit the responsibility to identify and dismantle health inequities at the coalface, today. I welcome constructive engagement in crafting durable solutions that will serve us far beyond the near horizen. None.
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.
How this classification was reachedexpand
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".