Justification and accounting: applying sociology of worth to accounting research
Bibliographic record
Abstract
Purpose The purpose of this paper is to introduce and illustrate the insights of the sociology of worth as advanced by sociologist Luc Boltanski and his collaborator economist/statistician Laurent Thévenot in their works, including their path‐breaking book De la justification published in 1991. Design/methodology/approach The paper explores the basic tenets of this “new sociology” and draws on it to render a reinterpretation of Ansari and Euske's study of cost accounting in a military depot. Findings The sociology of worth complements extant sociological approaches to accounting by providing a language and a conceptual tool‐box for understanding the multiple rationalities in which accounting is implicated. In addition, given its pragmatic micro level approach to accounting, it has the potential to act as a bridge between institutional theory and practice theory. Originality/value This paper is the first known to render an extensive discussion of Boltanski and Thévenot's work in the accounting literature and to apply insights from this work to accounting 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 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.003 | 0.054 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".