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Record W7028645304

Evaluation of a Nutrition-Based Peer Education Program

2023· dissertation· en· W7028645304 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Languageen
FieldMathematics
TopicMathematics and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsProgram evaluationVariety (cybernetics)Pilot programResource (disambiguation)Data collectionKey (lock)
DOInot available

Abstract

fetched live from OpenAlex

The Healthy Eating Volunteer (HEV) Program, which began in March 1997, was developed to establish a network of volunteers from the general public with practical skills to promote healthy eating in Saskatoon. The HEV Program set out nine objectives it wished to accomplish in its first year. This research project was framed to evaluate how well the HEV Program met these objectives.\n\nThis research study was a program-based, goal-oriented evaluation. Data were collected from: the researcher; the 20 HEVs; the Nutrition Resource and Volunteer Centre (NRVC) staff; and the users of HEV services. Data collection consisted of interviews with program participants and a review of HEV/NRVC documents.\n\nThe HEV Program evolved quite differently from its original plan. As the year unfolded, there was a shift in emphasis away from a peer education program to one that was providing volunteer opportunities in the area of nutrition. The demand for the services of the HEVs was not as great as was originally anticipated and this affected the number and types of projects the HEVs completed during the year. There was a wide variety in the level of involvement by HEVs and program communication to the HEVs.\n\nThe planning form sent out to all HEVs in the spring of 1997 turned out to be a key management tool of the program; however, not all HEVs completed it. The HEV Coordinator was a key factor in the successes attained by the HEV Program but the program did not have adequate coordinator support in place to manage all the HEVs.\n\nEven though the HEV Program evolved very differently from how it was first planned, almost all of the subjects were satisfied with the HEV Program. While it can be said that the HEV Program met 3 out of 9 objectives, it did not meet 3 out of 9, and the data were inconclusive for the other 3. The goals and objectives of the HEV Program no longer match the function and activities of the current program and this mismatch makes the results of the evaluation of the HEV Program challenging to interpret.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.275
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 teacher head, not a consensus.

Study designQualitative
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
Published2023
Admission routes1
Has abstractyes

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