Is Institutional Research on Management Accounting Degenerating or Progressing? A Lakatosian Analysis*
Bibliographic record
Abstract
ABSTRACT Adopting a Lakatosian perspective, this paper asks whether management accounting (MA) research using institutional theory can be described as a degenerative or progressive research program. Motivated by similar critical debates about the larger institutional research program in organization studies, I map the evolution of institutional research on MA with an eye to its theoretical contributions to the accounting literature as well as this larger research program. I conclude that this body of research has offered important, progressive extensions to the accounting literature and, to a lesser extent, the larger institutional research program. However, there is also evidence of many MA scholars using institutional theory in ways that produce degenerative tendencies. These degenerative tendencies are, in large part, due to the persistent proclivity of researchers to place overly one‐sided emphasis on the role of either human agency or preexisting institutions in explaining the process of (de‐)institutionalization and may, at worst, cause functionalist assumptions to be smuggled back into institutional analyses in ways that threaten the hard core of the institutional research program. I discuss how these tendencies can be rectified in future research and how institutional research on MA can be further developed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.004 | 0.043 |
| Scholarly communication | 0.014 | 0.023 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".