A Study Protocol for the EATing in a GENdered World (EatGen) Study
Bibliographic record
Abstract
This study will explore the development of a gender inclusive food literacy program targeting teens. To do this, three objectives will be investigated: 1. Teens’ perception of how social influences (parents, peers and the media), cognitive factors (motivation and self-efficacy), and gender norms influence eating; 2. Consider if social influences become more prominent following the onset of puberty; and 3. Evaluate whether targeting gender specific pressures improves the outcomes of a food literacy programs among teens. Twenty structured one-on-one interviews will be used to explore teens’ perspectives of how gender norms, cognitive factors and social influences impact eating (objective 1). Teen participants (13–18 years) will be recruited from a single school in Vancouver (BC, Canada). Data will be used to inform the variables of interest to include in a larger cross-sectional survey for teens from across Canada (n = 300). The survey will collect information on teens’ eating practices, Tanner stage of development, self-efficacy, and motivation to further explore the role how social pressures for eating practices may change following puberty (objective 2). Findings from objectives 1 and 2 will guide the development of a 50-hr gender inclusive food literacy tool that aims to improve teens functional, relational and systems competencies (i.e., food literacy skills). Qualitative results will be analyzed for emerging higher order themes (objective 1). Themes will be described by teens’ self-reported gender and biological sex. Quantitative findings from cross-sectional surveys will be analysed by sex and gender as well using t-tests or chi-squared tests. Differences based on Tanner stage of development will also be considered (objective 2). The food literacy tool will be piloted in 30 teens in a pre-post design (3 months) to investigate if teens’ food literacy skills (i.e., functional, relational and systems competencies) change favorably (objective 3). Findings from this work will help clarify how gender-based mechanisms influence teens’ eating practices. This knowledge will aid in the development of gender inclusion food literacy programs for teens This work is a part of A Deslippe's doctoral dissertation. Her studies are funded by the University of British Columbia.
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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 | 0.049 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.145 | 0.040 |
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".