The lived experience of Pacific Island women with a “big body” size
Bibliographic record
Abstract
This phenomenological study explored the lived experience with "big body" size of Pacific Island women who migrated to Hawaii. Giorgi’s descriptive phenomenological approach was utilized in this study. A purposive sample included six Pacific Island women. Five of the six women had migrated to Hawaii from the island nations of Micronesia. The sixth participant was a Native Hawaiian who had lived in Micronesia and had returned to Hawaii. The collection and transcription of data were done by the first author. Data were categorized into themes independently by the three authors and bracketing was maintained throughout the study. The women identified the dichotomy of "big body" versus "small body" and the connotation of each body size in how they viewed the world around them. They shared their lifestyle and transitional changes in trying to adapt and ‘fit’ into the new lifestyle in Hawaii. These changes impacted their eating habits and work schedule, level of activity, and financial security. The women identified biopsychosocial concerns in their lives and the need to re-evaluate their "big body" size in relation to their health and physical and psychosocial changes. Implications for future research are to include a diverse representation of women from island countries within the Pacific Basin. The results of this study provided valuable information related to cultural relevance and sensitivity in working with Pacific Island women in managing their health.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".