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Record W2513314600 · doi:10.1111/dme.13255

Review of research grant allocation to psychosocial studies in diabetes research

2016· review· en· W2513314600 on OpenAlexaffabout
Allan Jones, Michael Vallis, Debbie Cooke, Frans Pouwer

Bibliographic record

VenueDiabetic Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicinePsychosocialDiabetes mellitusGerontologyFamily medicinePsychiatryEndocrinology

Abstract

fetched live from OpenAlex

AIMS: To estimate and discuss the allocation of diabetes research funds to studies with a psychosocial focus. METHODS: Annual reports and funded-research databases from approximately the last 5 years (if available) were reviewed from the following representative funding organizations, the American Diabetes Association, the Canadian Diabetes Association, Diabetes Australia, Diabetes UK, the Dutch Diabetes Research Foundation and the European Foundation for the Study of Diabetes, in order to estimate the overall proportion of studies allocated research funding that had a psychosocial focus. RESULTS: An estimated mean of 8% of funded studies from our sample were found to have a psychosocial focus. CONCLUSIONS: The proportion of funded studies with a psychosocial focus was small, with an estimated mean ratio of 17:1 observed between funded biomedical and psychosocial studies in diabetes research. While several factors may account for this finding, the observation that 90% of funded studies are biomedical may be partly attributable to the methodological orthodoxy of applying biomedical reductionism to understand and treat disease. A more comprehensive and systemic whole-person approach in diabetes research that resembles more closely the complexity of human beings is needed and may lead to improved care for individuals living with diabetes or at risk of diabetes.

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)0.064
metaresearch head score (Gemma)0.405
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.445
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0640.405
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0030.006
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.685
GPT teacher head0.669
Teacher spread0.016 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

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

Citations11
Published2016
Admission routes2
Has abstractyes

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