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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. This 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. The 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. The 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. Even 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 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)0.024
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.032
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 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
Published2023
Admission routes1
Has abstractyes

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