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Record W4399450394 · doi:10.55016/ojs/ajer.v60i4.55975

Problematizing the Relationship between Rural Small Schools and Communities: Implications for Youth Lives

2015· article· en· W4399450394 on OpenAlexvenueno aff
Hernán Cuervo

Bibliographic record

VenueAlberta Journal of Educational Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSociologyPluralVitalityPoliticsHegemonyGender studiesSocial scienceEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Small schools are often the hub of many rural communities. In the school space, a multiplicity of social, economic and political relationships are sustained, which enhance the vitality of the community. As such, the relationship between small schools and communities is often presented as a powerful one; however, too often as a harmonious, natural and simple construction. This paper article argues that when education, youth and communities are defined through apparently simple, universal, natural and neutral conceptualizations, these are commonly based on prescribed norms that reflect the dominant values of an hegemonic majority. These homogeneous and universal conceptualizations of education, youth and community serve to legitimize processes of inequality and marginalization, and to undermine the goals these aim to contribute to. This article draws from disciplines such sociology of youth, education, rural studies and political theory to problematize the relationship between small schools and communities in rural spaces by analyzing the intersection of education and youth policies, as constructed by neoliberal policies, and the idea of community as presented by communitarians. It argues for the need to rethink the relationship between small schools and communities towards a more plural and socially just one that overcomes processes of exclusion and marginalization.

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)0.005
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.576
GPT teacher head0.528
Teacher spread0.047 · 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 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

Citations7
Published2015
Admission routes1
Has abstractyes

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