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Financial Management Capacity of Principals and School Governing Bodies in Lebowakgomo, Limpopo Province

2015· article· en· W2556726760 on OpenAlexaboutno aff
Lourens Johannes Erasmus Beyers, Tekedi Mohloana

Bibliographic record

VenueInternational Journal of Educational Sciences · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsAuditAccountabilityCorporate governanceBusinessFinancial managementFinancial literacyFinanceAccountingQuarter (Canadian coin)BookkeepingPublic relationsPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

The South African Schools Act (SASA) 84 of 1996 devolves management of state-allocated funds to school governance and management structures. However, school principals and school governing bodies (SGB’s) are often not aware of their responsibilities and liabilities when it comes to finances and accountability. This study investigated the extent of SBG’s and principals’ financial responsibilities and whether or not they are aware of and properly equipped to undertake financial management in their schools. This study found that the challenges include a lack of effective training of principals and SGB members, especially treasurers, by district-based personnel who themselves often lack financial literacy and basic knowledge of bookkeeping. Since financial management and skills play a significant role in improving educationand enhancing effective decision-making at all levels of school governance, the study recommends regular and thorough training of school principals and other SGB members. It also suggests the permanent placement of auditors at District offices to audit schools’ books each quarter. Other recommendations include that Department of Education’saudit processes should demand verifiable evidence to justify any expenditure.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.076
GPT teacher head0.401
Teacher spread0.325 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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