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Record W2266369372 · doi:10.5206/cie-eci.v44i2.9276

‘Successful’ Alternative Education: Still Reproducing Inequalities? The Case of the Community School Program in Egypt

2015· article· en· W2266369372 on OpenAlexaffvenue
Lucy El-Sherif, Sarfaroz Niyozov

Bibliographic record

VenueComparative and International Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMainstreamMathematics educationState (computer science)Quality (philosophy)SociologyPolitical sciencePedagogyPublic relationsEconomic growthPsychologyComputer scienceEconomics

Abstract

fetched live from OpenAlex

Community schools are an alternative form of education that center on partnerships between the community and/or the state, aid organizations, and non-governmental organizations. The Community School Program (CSP) in Egypt sparked a social movement in education in that country, with disparate actors all coalescing around the CSP as an alternative, empowering model of education. This study examined the relationship between the CSP and the dynamics that formed, shaped and co-opted it through in-depth interviews and observations. Our analysis examined the program’s processes and legacies on its former students. The study found that critical factors in the program’s success were its cost for the students, physical proximity, and quality teaching. After completing the program, these students faced significant challenges in mainstream secondary education. The CSP model is now converging with mainstream education. The interplay of national and global discourses shaped the CSP’s formation and continue to shape students’ social and academic learning through the evolution of its program.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.012
Scholarly communication0.0070.005
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.168
GPT teacher head0.478
Teacher spread0.310 · 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 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
Published2015
Admission routes2
Has abstractyes

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