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Record W2520023971 · doi:10.1080/03054985.2016.1220087

The myth of free and barrier-free access: India’s Right to Education Act—private schooling costs and household experiences

2016· article· en· W2520023971 on OpenAlexaff
Prachi Srivastava, Claire Noronha

Bibliographic record

VenueOxford Review of Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsUniversity of Ottawa
FundersEconomic and Social Research Council
KeywordsDisadvantagedGovernment (linguistics)SlumSchool choiceBusinessEconomic growthDemographic economicsEconomicsPolitical scienceSociologyPopulationLaw

Abstract

fetched live from OpenAlex

We examine relative household costs and experiences of accessing private and government schooling under India’s Right of Children to Free and Compulsory Education Act, 2009 in the early implementation phase. The Act deems that no child should incur any fee, charges, or expenses in accessing schooling. Private schools are mandated to allocate 25% of their seats for free via ‘freeships’ for socially and economically disadvantaged children. Furthermore, the Act has a number of provisions attempting to ease barriers to admission and entry to all schools, including private schools. This paper reports household-level data on the schooling patterns, experiences, and perceptions in one Delhi slum accessing schooling based on a survey of 290 households and 40 semi-structured household interviews. We found very low instances of children with private school freeships. Furthermore, children in ‘free’ private school seats incurred the second highest costs of accessing schooling after full-fee-paying students in relatively high-fee private schools. Finally, households accessing freeships and higher-fee schools experienced considerable barriers to securing a seat and admission.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.014
GPT teacher head0.311
Teacher spread0.297 · 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 designNot applicable
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

Citations34
Published2016
Admission routes1
Has abstractyes

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