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Record W2144841474 · doi:10.22230/ijepl.2010v5n2a66

Teachers as Partners in the Prevention of Childhood Obesity

2010· article· en· W2144841474 on OpenAlexvenueno aff
Mozhdeh B. Bruss, Linda L. Dannison, Jackie Quitugua, Rosa T. Palacios, Judy McGowan, Timothy Michael

Bibliographic record

VenueInternational Journal of Education Policy and Leadership · 2010
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersWestern Michigan UniversityLarry L. Hillblom Foundation
KeywordsCommonwealthGeneral partnershipCurriculumChildhood obesityPsychological interventionMedical educationPublic healthPsychologyMedicinePublic relationsPedagogyPolitical scienceNursingObesity

Abstract

fetched live from OpenAlex

This paper presents a community-school-higher education partnership approach to the prevention of childhood obesity. Public elementary school personnel, primarily teachers, participated in the design and delivery of a curriculum targeting primary caregivers of 8-9-year-old children. Theoretical framework and methodological approaches guided the development of a cognitive behavioral lifestyle intervention targeting childhood obesity prevention in the Commonwealth of the Northern Mariana Islands (CNMI), a U.S. commonwealth. This project demonstrated that in populations with health disparity, teachers can be a valuable and accessible resource for identifying key health issues of concern to communities and a vital partner in the development of parent and child interventions. Teachers also benefited by gaining knowledge and skills to facilitate student and parent learning and impact on personal and familial health. Successful community-school-higher education partnerships require consideration of local culture and community needs and resources. Moreover, within any community-school–higher education partnership it is essential that a time sensitive and culturally appropriate feedback loop be designed to ensure that programs are responsive to the needs and resources of all stakeholders, and that leaders and policymakers are highly engaged so they can make informed policy decisions.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.274
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.067
GPT teacher head0.402
Teacher spread0.335 · 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 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

Citations27
Published2010
Admission routes1
Has abstractyes

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