Expanding the limits of sex: a systematic review concerning food and nutrition in transgender populations
Bibliographic record
Abstract
Objective: To examine the literature and identify main themes, methods and results of studies concerning food and nutrition addressed in research on transgender populations. Design: A systematic review conducted through July 2020 in the MedLine/PubMed, Scopus and Web of Science databases. Results: Of the 778 studies identified in the databases, we selected thirty-seven. The studies were recent, most of them published after 2015, being produced in Global North countries. The most often used study design was cross-sectional; the least frequently used study design was ethnographic. Body image and weight control were predominant themes (n 25), followed by food and nutrition security (n 5), nutritional status (n 5), nutritional health assistance (n 1) and emic visions of healthy eating (n 1). Conclusions: The transgender community presents body, food and nutritional relationships traversed by its unique gender experience, which challenges dietary and nutritional recommendations based on the traditional division by sex (male and female). We need to complete the lacking research and understand contexts in the Global South, strategically investing in exploratory-ethnographic research, to develop categories of analysis and recommendations that consider the transgender experience.
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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 | 0.014 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".