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Record W2594356081 · doi:10.5539/jel.v6n2p283

Basic Education in Ivory Coast: From Education for All to Compulsory Education, Challenges and Perspectives

2017· article· en· W2594356081 on OpenAlexvenueno aff
Rassidy Oyeniran

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Educational Policies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsDisadvantagedCompulsory educationEconomic growthContext (archaeology)General partnershipMillennium Development GoalsPolitical scienceConstitutionHigher educationEducation policyPovertyPublic relationsSociologyGeographyEconomics

Abstract

fetched live from OpenAlex

Ivorian authorities, for years, are employing various strategies as part of reforms to ensure universal education in Ivory Coast (Cote d’Ivoire). In this regard, great efforts are done each year through public funding and partnership development support to face the challenge of Education for All whose term of the implementation was 2015. The objective of this paper is to investigate the various facets of Education for All in Ivory Coast and the implications of the implementation of compulsory education, which is the new challenge of Ivorian education system. How to bridge the gap of schooling? What measures would be effective to ensure 100% enrolment as multiple factors constitution obstacle to the achievement of the Millennium Development Goals (MDGs). Using qualitative methods based on relevant data from books, articles and others secondary sources from reports as well as other information from the World Wide Web, this study examined the current issues of Education for All in the post-crisis context. Although immense sacrifices have been done to Education for All, persistent factors unlikely still limit its implementation. The success of the compulsory education is possible whether the State invests more resources in Education and creates well conditions for access to education in all areas of the country, paying more attention to marginalized groups such as children with disadvantaged social backgrounds and girls. In conclusion part of this study possible solutions and recommendations that can overcome the persistent issues of Education for All are provided for higher educational policy prospects.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.041
GPT teacher head0.386
Teacher spread0.345 · 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 designOther design
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

Citations13
Published2017
Admission routes1
Has abstractyes

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