Economic Expertise in Postcapitalist Democratic Economic Planning
Bibliographic record
Abstract
Postcapitalist democratic economic planning (DEP) seeks to democratize economic decision-making. In response to the failures of central planning, DEP is vigilant lest the emergence of some new elite subvert its democratic and egalitarian aspirations. This article considers the possibility that economic expertise intended to support DEP may be means through which new elites are covertly encouraged. DEP advocates seek to safeguard DEP processes from elite control by proposing institutional oversight structures combined with enhanced subjective oversight capacities. In the case of economic expertise, we contend that these responses mitigate the possibility that economists’ analyses will have preferential implications but do not resolve this antidemocratic possibility. Economic expertise poses a problem of democratic accountability because its technical opacity impedes democratic oversight, thus enabling the covert design of economic analysis in ways that favour some groups over others. We conclude by arguing that reconsidering economic expertise in postcapitalism can attenuate this tension.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".