(Non) coverage of sustainability within the French professional accounting education program
Bibliographic record
Abstract
Purpose This study seeks to identify how professional accountants in France are educated in sustainability; we examine the French accounting programs in regard to sustainability accounting education recommendations. Design/methodology/approach We analyze a variety of documents to ascertain what comprises the typical accounting education program in France. Additionally, we conduct five interviews of various stakeholders to understand the importance of sustainability accounting and education in the French context. Findings We note an interesting paradox in the French context: while the government requires the reporting and auditing of corporate sustainability information, we find that sustainability is not greatly present in the government-funded French accounting education program. We determine that the government’s power in setting the education agenda combined with its budget restrictions and ability to defer responsibility to other parties has resulted in this paradox in the French setting. Practical implications This research draws attention to the consequences of society ignoring sustainability education for professional accountants. Social implications This paper contributes to the discussion on how to educate responsible professional accountants and the implications for the planet if accountants are not trained in sustainability. Originality/value This research contributes to the important domain of sustainability accounting education. We also explore additional implications for the accounting profession and the general public.
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 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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".