The ‘Freshman 5’: A Meta-Analysis of Weight Gain in the Freshman Year of College
Bibliographic record
Abstract
OBJECTIVE: (1) To use the available research to estimate the amount of weight gained by college freshman during their first year of college. (2) To identify potential predictors of freshman weight gain. METHODS: A meta-analysis was conducted in November 2008. The analysis focused on articles published in English scientific journals between 1985 and 2008 available on the MEDLINE, Web of Science, and PsycINFO databases and excluded studies of weight change over periods beyond freshman year. RESULTS: Twenty-four studies met the inclusion criteria. Based on a pooled sample of 3,401 cases, mean weight gain was 3.86 (95% confidence intervals [CI] = 3.81-3.91) lbs. Potential contributors to gain were recent dieting, high baseline weight, and psychological stress. CONCLUSIONS: The first year of college is a period of vulnerability for weight problems. Further research is needed to better understand freshman weight gain and devise appropriate prevention strategies based on predictors of gain.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.024 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".