From crisis to the everyday: Shouldn't we all be writing economies?
Bibliographic record
Abstract
This commentary explores the politics of writing about the economy in a culture, society, and discipline that tends to prioritize masculinist (and white) theories and definitions of economy over embodied experiences of people living their everyday lives. Inspired by Timothy Mitchell's problematization of the economy as an object of analysis, we press further on the seemingly singular unit of “the” economy and who is allowed to define it as such. We are animated by questions of who is considered an expert on the economy and how, or by whom, crises in the economy are recognized. Drawing from our own writing experiences during the pandemic and from social movements we research, we argue for alternate ways of thinking about experiences of and expertise on the economy. In reckoning with how social movements speak to power in a bid to transform economies, we consider the role of economic geography in the economy of writing and knowledge production surrounding “the economy” itself. We make the case for a more public economic geography grounded in the social and economic embeddedness of knowledge production, the material consequences of who gets to define what is economically “important,” and the potential for this expertise to be located anywhere.
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.029 |
| Scholarly communication | 0.019 | 0.021 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".