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Record W4400787835 · doi:10.47381/aijre.v34i2.715

Bridging the Gap Between Community Schools and Rural Communities in Nepal Using Participatory Action Research

2024· article· en· W4400787835 on OpenAlexfundno aff
Salpa Shrestha, Megh Raj Dangal

Bibliographic record

VenueAustralian and International Journal of Rural Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
FundersInternational Development Research Centre
KeywordsBridging (networking)Participatory action researchCitizen journalismRural communityGeographyAction researchEnvironmental planningPolitical scienceSocioeconomicsSociologyPedagogyAnthropologyComputer science

Abstract

fetched live from OpenAlex

This paper explores the engagement of parents with out-of-school children through community-based participatory action research in a rural community in Nepal. This study addresses the connection gap between local communities and community schools, which has resulted in consequences such as inconsistent attendance among students and low educational expectations among parents. By investigating the processes of formulating an action plan by a parent-led action group and analysing its execution, the research aimed to understand how participatory action research can foster a stronger bond between community schools and parents, thereby enhancing parental involvement in children’s education. The study draws on Mezirow’s transformative learning theory, incorporating concepts from Habermas’s public sphere and Freire’s notion of conscientization. It specifically focuses on the action group’s monthly meetings held over nine months and the collaborative outcomes that resulted. By emphasising targeted interventions, collaboration and a departure from deficit-focused approaches, the findings propose effective strategies for bridging the gap between community schools and rural communities in Nepal.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.411
GPT teacher head0.531
Teacher spread0.120 · 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 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

Citations1
Published2024
Admission routes1
Has abstractyes

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