Older women's perceptions of ideal body weights: the tensions between health and appearance motivations for weight loss
Bibliographic record
Abstract
This paper explores older women's evaluations of their weight as well as the perceived merits and detriments of weight gain and weight loss in later life. Using data from semi-structured interviews with 22 community-dwelling women aged 61 to 92 years, I examine the meanings that the women attribute to dieting, desired body weights and obesity. The women frequently offer unsolicited accounts for why they have gained or lost weight over time, and disclose their perceptions of and reasons for needing to alter their current body weights. I probe the tensions between weight loss for health concerns versus appearance goals. The women express dissatisfaction with their weight gain in terms of their physical appearance. However, they also tend to describe the need to lose weight in terms of health risks and benefits rather than in terms of approximating the beauty ideal or achieving a desired body size and shape. Health tends to be described as a valid justification for being concerned with one's weight, while an appearance orientation is deemed to be indicative of vanity. Many of the women suggest that while the health benefits of weight loss are often the stated reason for losing weight, the perceived appearance dividends are the key motivation behind altering one's body weight in later life.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".