Not on the ruins, but with the ruins of the past – Inertia and change in the financial reporting field in a transitioning country
Bibliographic record
Abstract
We investigate how local actors in the Romanian financial reporting field mobilize their indigeneity to enact and operationalize transnational financial reporting models in a context where neoliberal ideas represent a substantive change in respect to the past. We mobilize interviews with local key actors, evidence from multiple data sources, and Bourdieu’s concept of habitus to investigate how inertia and change are intertwined. We explain how the Romanian state continues to draw on and reproduce the local accounting inclinations inherited from communist times. At the macro level, the state’s actions (through the role of financial reporting regulator) suggest a strong agency exerted in the backstage, paralleling the appearance of accepting International Financial Reporting Standards (IFRS) in the frontstage. At the micro level, where rules are operationalized, indigenous professionals deal with their historically created habitus and with various destabilizing influences from newcomers to the financial reporting field, which reflects diverse relationships and power imbalances between nascent actors of a market economy. We show that habitus is critical in understanding the complicated dynamics of inertia and change in accounting practices. Our results illustrate a web of improvisation, imitation, hybridization, and reinterpretation of both locally traditional and Western principles as local accounting rules and practices become global and remain local.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.035 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".