Counter accounts of profit: outrage to action through “just” calculation
Bibliographic record
Abstract
Purpose Profit is often moralized by activists, but scant research has carefully examined what profit is for these activists or how they use it to create a more just world. The purpose of this paper is to investigate how social movements use counter accounts of profit as tools of resistance. Design/methodology/approach A multiple case study design, informed by framing theory, is used to trace the framing of profit from activists’ counter accounts to actions they precipitated. Specifically, the study examines counter accounts of profit from the UK abolition movement, Médecines Sans Frontières access to essential medicines campaign and Brigitte Bardot Foundation’s opposition to the Canadian seal hunt, and how their framings of profit influenced change. Findings Activists reframe profit to create visibilities and bridges to the suffering of distant others. Reframing the calculation and boundary of profit is a strategy to elicit moral outrage, hope and ultimately a more just world. Through these reframings, activists in three different social movements were able to change the possibilities of who and what can be profitable, and how. Social implications The inherently incomplete nature of accounting frames give rise to accounting’s vulnerability to non-accountants to assert their views of a moral profit. Accounting therefore is both a means of control at a distance but also “emancipation at a distance.” Originality/value Scholars have asserted that accounting can be used for resistance, few studies have examined how. By examining how activists assert what profit is – and should be – the paper documents and theorizes profit as contested and highlights accounting’s emancipatory potential.
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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.070 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".