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Record W4205919556 · doi:10.5539/ass.v18n1p47

The Effect of Board Characteristics on Real Activities Manipulation in Tunisian Banks

2021· article· en· W4205919556 on OpenAlexvenueno aff
Amina Zgarni, Hassouna Fedhila

Bibliographic record

VenueAsian Social Science · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceAccountingRevenueEarnings managementEarningsBusinessOn boardPanel dataEquity (law)Independence (probability theory)EconomicsFinancePolitical scienceEconometricsLawEngineering

Abstract

fetched live from OpenAlex

The succession of financial scandals and resounding bank failures that characterized the economic environment over the past three decades have given more weight to governance mechanisms. As such, considered to be one of the most important internal governance mechanisms, the board of directors has shown its strengths in controlling earnings manipulation, in particular those linked to real activities. The aim of this paper is to examine the effect of board characteristics on real earnings management. Using panel data econometrics, on all Tunisian commercial banks over the period 2008-2019, we show that board gender diversity has a disciplinary role in real earnings management as measured by discretionary revenue on equity securities. However, we show that board independence increases the real earnings management. As for board size, board duality, as well as the number of meetings carried out per year by the board of directors, we prove that they have no significant effect on real earnings management.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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