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Record W2792392806

Body dissatisfaction, concerns about aging, and food choices of baby boomer and older women in Manitoba

2012· dissertation· en· W2792392806 on OpenAlexfundaboutno aff
Catherine E. Marshall

Bibliographic record

VenueMspace (University of Manitoba) · 2012
Typedissertation
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaManitoba Rural Adaptation CouncilManitoba Agriculture, Food and Rural DevelopmentManitoba Health Research Council
KeywordsBaby boomersGerontologyPsychologySuccessful agingMedicineEconomicsDemographic economics
DOInot available

Abstract

fetched live from OpenAlex

The objectives of this research project were to (1) explore perceptions and experiences related to body dissatisfaction, aging, and the use of body work practices among baby boomer and older women; and (2) explore healthy eating attitudes and barriers, food choice influences, dieting behaviours, and food product usage/attitudes among these women. Fourteen focus groups with baby boomer and older women were conducted in urban and rural areas of Manitoba (n=137). Participants also completed a questionnaire and height and weight measurements. Body image, aging and food were intimately connected in women’s lives. Feelings about the body were closely connected to the experience of aging and perceptions of the body influenced food choices and attitudes. This thesis adds value to the existing literature by exploring the connections between aging, food, and the body, from the perspectives of baby boomer and older women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.912

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.016
GPT teacher head0.258
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes2
Has abstractyes

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