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Record W4401823940 · doi:10.1111/1467-8551.12865

Discretion in the Governance Work of Internal Auditors: Interplay Between Institutional Complexity and Organizational Embeddedness

2024· article· en· W4401823940 on OpenAlexafffund
Vikash Kumar Sinha, Marika Arena, Eduardo Schiehll

Bibliographic record

VenueBritish Journal of Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting and Organizational Management
Canadian institutionsHEC Montréal
FundersSocial Sciences and Humanities Research Council of CanadaEuropean Commission
KeywordsEmbeddednessSituatedDiscretionCorporate governanceAgency (philosophy)BusinessAuditAccountingWork (physics)Public relationsSociologyPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

Abstract This study examines which factors facilitate (obstruct) the discretion exercised by ground‐level governance actors, such as internal auditors, in justifying their governance work. To achieve this objective, we rely on two complementary theoretical perspectives. One perspective proposes that the organizational embeddedness of ground‐level governance actors, ordained by high‐level governance actors (such as the board of directors), obstructs their discretion. In contrast, the other perspective, building on institutional complexity, propounds that multiple institutional demands facilitate the situated agency and discretion of ground‐level governance actors. Consistent with the emerging multilevel research on institutional complexity, we combine these two perspectives by including both the structural and static meso‐level factors (i.e. organizational embeddedness) as well as actors' situated agency. Utilizing three comparative cases, we demonstrate that internal auditors' ability to exercise discretion is facilitated (obstructed) when organizational embeddedness enables (constrains) the cohabitation of multiple institutional logics at the organizational level. In doing so, we identify organizationally situated agency as an underlying factor driving internal auditors’ justification approaches in their governance work.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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