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Migration and nutrition

2018· book-chapter· en· W2902640148 on OpenAlexaff
Janice L. Thompson, Joy Merrell, Barry Bogin, Hannah Maria Jennings, Michael Heinrich, Vanja Garaj, Diane M. Harper, Bablin Molik, Jasmin Chowdhury

Bibliographic record

VenuePolicy Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsPopulation ageingGerontologyHealthy ageingOlder peopleAgeingPopulationPsychologyGeographyEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

This chapter describes Project MINA, an intergenerational and transnational project using a mixed-methods approach to investigate migration, nutrition, and ageing in two generations of Bangladeshi women living in the UK or Sylhet, Bangladesh. Results indicate that varied migration histories and changing family structures play an important role in influencing nutritional status, perceived and actual health status, and future health and social care needs of ageing Bangladeshis in the UK. Future research should focus on developing culturally and linguistically tailored research tools to assess dietary intake and eating behaviours within this population, and examine the complex interplay between family dynamics, cultural norms and social influences that impact the ability of older Bangladeshi adults to eat more healthfully and engage in physical and social activities that promote healthy ageing.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.319
Teacher spread0.277 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

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