Women in Nephrology-India: One-Year-old, Yet Miles to Cover
Bibliographic record
Abstract
One-Year-old, Yet Miles to CoverTo the Editor: Women in Nephrology-India (WIN-India) was established in August 2021 to provide mentorship and a support system to the Indian nephrology community. 1The organization has since conducted webinars, quizzes, symposiums, case discussions, and sent out newsletters.We evaluated the status and quality of the academic content of WIN-India activities in India from August 30, 2021 to July 31, 2022, via an online survey.Participants were nephrologists, residents, dieticians, dialysis technicians, and nurses.A total of 350 responses were received, and the demographics are listed in Table 1.Of the total respondents, 90% were aware of WIN-India and social media was the most popular source of information.On a scale of 1 to 10, the academic content of WIN-India activities was rated at 10 by 35.2% and at 9 by 38.2%.Sixty-two percent of the respondents reported that WIN-India webinars were beneficial to their practice or research projects, 83% said that WIN-India is a step forward toward improving education, and 80% were interested in its activities.The question about feedback and weaknesses was unanswered by 32%.The main feedback was to increase social media coverage.Some respondents suggested an international collaboration to boost academics.There were suggestions to revamp WIN-India website, encourage academic work by younger faculty, improve academics, and not just address gender bias.Starting a YouTube channel and advocacy sessions for all stakeholders were suggested.Establishing a national registry, discussing the challenges faced by women with kidney problems, and participating in government policy-making were important suggestions.The result of the survey is summarized in Figure 1.This survey was carried out as a scorecard for WIN-India to assess if it had succeeded in its ideals and to identify potential areas of improvement.Notably, 70% of the respondents rated the academic content of WIN-India activities highly.Although its main goal is to provide mentorship to women, it has been inclusive of all sexes, with participation of men as members and speakers.International collaboration to learn, network, and exchange knowledge was a welcome suggestion.WIN-India organized its first international conference (Women in Nephrology-India Conference) with renowned speakers from around the globe.Thus, in the first year of its inception, WIN-India has successfully provided a platform for academics, mentoring, networking, advocacy, and leadership development.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".