Justifying Accounting Change Through Global Discourses and Legitimation Strategies. The Case of the UK Central Government
Bibliographic record
Abstract
Accounting has been viewed, especially through the lens of the recent managerial reforms, as a neutral technology that, in the hands of rational managers, can support effective and efficient decision-making. However, the introduction of new accounting practices can be framed in a variety of ways, from value-neutral procedures to ideologically charged instruments. Focusing on financial accounting, budgeting and performance management changes in the UK central government, and through extensive textual analysis and interviews in three government departments, this paper investigates: how accounting changes are discussed and introduced at the political level through the use of global discourses; and what strategies organisational actors subsequently use to talk about and legitimate such discourses at different organisational levels. The results show that in political discussions there is a consistency between the discourses (largely New Public Management) and the accounting related changes that took place. The research suggests that a cocktail of legitimation strategies was used by organisational actors to construct a sense of the changes, with authorisation, often in combination with, at the very least, rationalisation strategies most widely utilised. While previous literature posits that different actors tend to use the same rhetorical sequences during periods of change, this study highlights differences at different organisational levels.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.012 | 0.057 |
| Scholarly communication | 0.023 | 0.017 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".