The Architecture Of Management Account-ing Systems Change: A Multidimensional Approach
Bibliographic record
Abstract
We extend the model developed by Williams and Seaman [Williams, J. J. & Seaman, A. E. (2001). Predicting change in management accounting systems: national culture and industry effects. Accounting, Organizations and Society, 26, 443–460] and utilize the same sample of 93 Chinese family owned businesses to test the multivariate relationship between a set of operational effectiveness measures and a set of changes in management accounting and control systems components under the contingency effects of size, organizational capacity, intensity of competition and centralization. Significant relationships emerge for high intensity of competition, high centralization, and low and high levels of organizational capacity. Variables of major importance in these relationships converge to form two larger patterns of a structural and environmental nature, which are consonant with the core national cultural values of Singapore documented in the contemporary cross-cultural management control literature.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".