The diktat of concision: When accounting for words shrinks academic knowledge
Bibliographic record
Abstract
For the vast majority of accounting and management research journals, the length of submitted articles is now considered an essential criterion, and the watchword in this respect is: “keep it as short as possible!” Our goal in this essay is to highlight the potential damaging side-effects that this “diktat of concision” currently imposed on researchers can have on the creation of knowledge. We also seek to better understand how the current circumstances constitute a fertile ground for such a diktat to thrive despite its possible negative repercussions. As we advance in our reflection, we come to illuminate a set of possible resonances between (1) the academic writing style promoted by the “diktat of concision” and a context marked by: (2) the “McDonaldization” of research, (3) the persistent domination of the positivist approach in accounting and management academia, and (4) the increasing performatization of science. In sum, we endeavor to challenge the mythological edifice underpinning the voice of concision in the world of research.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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; a candidate call from one teacher head, 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".