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Record W4386030601 · doi:10.3390/children10081413

A Tale of Two Programs for Parents of Young Children: Independently-Conducted Case Studies of Workforce Contributions to Scale in Bhutan and Rwanda

2023· article· en· W4386030601 on OpenAlexaff
Frances E. Aboud, Karma Choden, Michael Tusiimi, Rafael Contreras Gomez, Rachel Hatch, Sara Dang, Theresa S. Betancourt, Karma Dyenka, Grace Umulisa, Carina Omoeva

Bibliographic record

VenueChildren · 2023
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill University
FundersLEGO FoundationBoston College
KeywordsWorkforceScale (ratio)PsychologyEconomic growthGeographyEconomicsCartography

Abstract

fetched live from OpenAlex

Two case studies of parenting programs, aiming to improve parenting practices and child development outcomes, and implemented by Save the Children/Ministry of Health/Khesar Gyalpo University in Bhutan and Boston College/University of Rwanda/FXB in Rwanda, respectively called Prescription to Play and Sugira Muryango, were conducted by an independent research and learning group. Implementation research focused on the workforce, a crucial but little-studied element determining the success of programs going to scale. Mixed methods were used to examine their training, workload, challenges, and quality of delivery. Health assistants in Bhutan and volunteers in Rwanda were trained for 10-11 days using demonstrations, role plays, and manuals outlining activities to deliver to groups of parents (Bhutan) or during home visits (Rwanda). Workers' own assessments of their delivery quality, their confidence, and their motivations revealed that duty, confidence, and community respect were strong motivators. According to independent observations, the quality of their delivery was generally good, with an overall mean rating on 10 items of 2.36 (Bhutan) and 2.44 (Rwanda) out of 3. The facilitators of scaling for Bhutan included institutionalizing training and a knowledgeable workforce; the barrier was an overworked workforce. The facilitators of scaling for Rwanda included strong follow-up supervision; the barriers included high attrition among a volunteer workforce.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.348
Teacher spread0.319 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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