Gender and decistion making in Neurology, an Argentinian study. (P5-12.005)
Bibliographic record
Abstract
Objective: Determine the distribution of hierarchical positions in neurology according to gender in Argentina Background: Even though in Argentina, 7 out of 10 medical students are women, 75% of postgraduate hierarchical positions are held by men. The representation of women in senior positions in Argentine neurology is unknown. Design/Methods: A cross-sectional study was carried out, an online form was sent to neurologists throughout Argentina. Responses were received from May to July 2021. The questionnaire included age, gender, family constitution, type of training in neurology, managementtraining, postgraduate degrees, type of institution (public or private) and desire to occupy a position of decision making. The T and Chi square test were used to compare continuous and categorical variables, respectively. Logistic regression was used to determine the association of multiple variables. Results: 383 responses were received, 63% were women from 23/24 provinces of Argentina. Women were younger than the men (41.9 ± 9.9 vs 44.9 ± 11.7 years, p = 0.009). The hierarchical positions were significantly lower in women than in men 25.5 vs 50.7%, p <0.001). There was a significant association between high-ranking positions and gender [OR 0.36 (CI95% 0.21–0.60), p <0.001], age [OR 1.07 (CI95% 1.04–1.10), p <0.001)], the desire to occupy that position [OR 3.48 (95% CI 1.95–6.21), p <0.001], management training [OR 1.88 (95% CI 1.01–3.51), p = 0.046] and postgraduate degree (OR 2.50 (95% CI 1.47–4.25), p = 0.001). Within young neurologists, hierarchical positions were directly correlated with age and inversely correlated with female gender, while in neurologists older than 55 years, age was not correlated with hierarchical positions, while gender inequities persisted. Conclusions: In Argentina, most senior positions are held by men. The female gender was associated with a lower probability of occupying decision-making positions regardless of other variables Disclosure: Maria Gaitan has received personal compensation in the range of $500-$4,999 for serving as a has received reimbursement for developing educational presentations and/or travel/accommodations stipends from with Merck SA, Merck-Serono Argentina, Biogen-Idec Argentina, Novartis Argentina, Roche Argentina,. Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Biogen. Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Merck. Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Genzyme. Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Roche. Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving as an Expert Witness for Merck, . Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving as an Expert Witness for Biogen. Celica Ysrraelit has received personal compensation in the range of $500-$4,999 for serving as an Expert Witness for Bayer. Celica Ysrraelit has received research support from Novartis. Laura Negrotto has received personal compensation for serving as an employee of Merck. Laura Negrotto has received personal compensation in the range of $0-$499 for serving as a Consultant for Entelai. Dr. Bruno has received personal compensation in the range of $0-$499 for serving as a Consultant for Biogen. The institution of Dr. Bruno has received research support from Paladin Labs. The institution of Dr. Bruno has received research support from Ipsen. Dr. Fernandez has nothing to disclose. Dr. Azcona has nothing to disclose. Maria Justich has nothing to disclose. Mariela Cabrera has nothing to disclose. Mrs. Rodriguez Perez has nothing to disclose. Marina Romano has nothing to disclose. Dr. Ibarra has nothing to disclose. Dr. Derosa has nothing to disclose. Guadalupe Bruera has nothing to disclose. Ms. Zavala has nothing to disclose.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".