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Record W1989643818 · doi:10.5539/ass.v9n1p209

Organizational Characteristics and Disclosure Practices of Non-profit Organizations in Malaysia

2012· article· en· W1989643818 on OpenAlexvenueno aff
Roshayani Arshad, Noorbijan Abu Bakar, Farah Haneem Sakri, Normah Omar

Bibliographic record

VenueAsian Social Science · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
FundersMinistry of Higher Education, Malaysia
KeywordsBusinessAccountingProfit (economics)Not for profitNon profitTransparency (behavior)Public relationsMarketingBusiness administrationEconomicsPolitical science

Abstract

fetched live from OpenAlex

The purpose of this study is to examine the influence of organizational characteristics on the extent of disclosures in the annual reports of non-profit organizations (NPO) in Malaysia. Organizational characteristics and the extent of disclosures are obtained from the content analysis of annual reports of 213 NPOs registered with Registrar of Societies in Malaysia for the financial period 2010. This study provides evidence that the overall extent of disclosure is low. Of the organizational characteristics, this study revealed significant positive relationships between size and some types of funds available to the NPOs. The significant positive relationships between certain types of funds and extent of disclosures in some parts of the annual reports indicate selective disclosure strategies by non-profit managers, thus reducing meaningful transparency in the non-profit sector. Nevertheless, it indicates that non-profit managers are using disclosures in annual reports in managing their inter-organizational relationships in ensuring continuous flow of resources to their organisations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
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 head0.017
GPT teacher head0.320
Teacher spread0.303 · 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

Citations21
Published2012
Admission routes1
Has abstractyes

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