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Record W3086418778 · doi:10.32628/cseit1949188

Right to Education Act-Challenges and Recommendation

2019· article· en· W3086418778 on OpenAlexaff
A. Vijaya

Bibliographic record

VenueInternational Journal of Scientific Research in Computer Science Engineering and Information Technology · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsComputer sciencePolitical scienceBusiness

Abstract

fetched live from OpenAlex

The right to education is one of the human rights, The right to education is written in Article 26 of the 1948 Universal Declaration of Human Rights .Education encourages us to supports monetary development, advance harmony in the general public, bring great administration, expel defilement, annihilate neediness, evacuate sexual orientation separation and imbalance ,causes us in making self-ward . Right to education is perhaps the best Act; our legislature has ever brought and changed youngsters into understudies. It gave a chance to the kids who can

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)0.026
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.115
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.009
Scholarly communication0.0120.017
Open science0.0030.004
Research integrity0.0180.014
Insufficient payload (model declined to judge)0.0350.006

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 head0.033
GPT teacher head0.353
Teacher spread0.320 · 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 designTheoretical or conceptual
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

Citations0
Published2019
Admission routes1
Has abstractno

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