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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 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)0.001
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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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