A Comparison of Canadian and Irish Views on a Set of Traditional and Advanced Management Accounting Techniques
Bibliographic record
Abstract
This study presents an analysis of the responses of accounting/financial management professionals regarding the usage of seven traditional and five advanced management accounting techniques. The respondents are senior accounting/financial executives employed in large Canadian companies and management accountants with membership of CIMA employed in Irish companies. The Canadian findings are consistent with the dominant usage of traditional techniques reported earlier for Ireland and suggest similar usage of management accounting techniques overall. The findings also suggest that the advanced techniques widely recommended in accounting texts and professional publications have not had a significant uptake in either country. In both countries, there are some techniques that differ in usage between small and large companies. For four traditional techniques and two advanced techniques there are very significant differences in usage between Canadian and Irish companies. Consistent results are found for analysis of the techniques individually and of traditional and advanced techniques as groups. Canadian and Irish companies can be differentiated based on their usage of management accounting techniques, even though there is an overall similarity in usage. Discriminant analysis using traditional techniques allows classification of companies as Canadian or Irish with a high level of accuracy, but the classification using advanced techniques is less reliable. In summary, the study shows that while there is a consistent pattern of usage in the two countries, there are also significant differences in the usage of specific techniques.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".