On affect and accounting inscriptions: a study of fair value in the making
Bibliographic record
Abstract
Purpose This paper aims to theorize the role of affect in shaping accounting numbers by studying accountants who specialize in the production of fair value measurements for intangibles. Design/methodology/approach Drawing on interviews with valuation specialists employed by public accounting firms, I investigate the circulation of affect in fair value measurement networks. While prior studies stress the coordinative potential of affect, I focus on affective clashes, as well as on the associations that are drawn between the specialists and other actors in response to these clashes. Findings The findings suggest that affect impacts the stability of accounting inscriptions, in that it plays a significant role in both the destabilization and the ultimate stabilization of valuation networks. Practical implications The proposed reframing of valuation work may allow regulators and other stakeholders to consider issues beyond pure cognitive bias and to recognize that interrelational affect is materially implicated – both favourably and unfavourably – in valuation outcomes. Originality/value The study reframes the issue of fair value measurement as one of stabilizing value inscriptions through clashes of passionate interests, rather than one of reducing individual bias at the valuator level. In addition, the study refines the concept of stability in actor-network theory by considering its significant interrelations with the affective dimension of networks and discusses certain issues in the current fair value literature.
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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 | 0.038 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.001 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".