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Record W2971764496 · doi:10.18535/ijsrm/v7i9.el01

Headteachers’ Perception of the Implementation of the Capitation Grant Scheme In The Sunyani West District of the Brong Ahafo Region

2019· article· en· W2971764496 on OpenAlexaboutno aff
Georgina Cate Foli, Owusu Afriyie

Bibliographic record

VenueInternational Journal of Scientific Research and Management (IJSRM) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsCapitationGovernment (linguistics)ImplementationQuarter (Canadian coin)BusinessPsychologyFinanceGeographyEngineering

Abstract

fetched live from OpenAlex

This study was conducted to find out head teachers' perception of the implementation of the capitation grant scheme in Sunyani West East District of the Brong Ahafo Region. The study specifically focused on explaining how head teachers conceptualised the concept of capitation grant scheme, the implementation process, and the challenges associated with the implementation of the scheme. A descriptive research design was adopted for the study, and a questionnaire and an interview guide were designed and administered to a sample of 40 head teachers from the district in the Region. The analysis of data revealed that 70.0% of thehead teachers had an in-depth understanding of the source of capitation grant as being from the Government. The study, among others, found that the main challenges confronting the smooth implementations of the scheme were delay in the release of funds and inadequate funds. It is recommended that Government should release adequate amount of the grant in good time (thus, before the beginning of each quarter) so that school heads will avoid pre-financing of school activities. Also, the Ghana Education Service should continue to train head teachers in financial management and administration for prudent use of funds.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.284

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.084
GPT teacher head0.432
Teacher spread0.348 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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