The Polanyi Moment, Decommodification of Labor and the Struggle for Full Employment: How the COVID-19 Crisis has Opened the Debate Over the Nature of the Fictitious Labor Market in Both the Industrialized and Developing World
Bibliographic record
Abstract
The purpose of this article is first to discuss how the so-called fictitious labor market has been analyzed historically, by studying the classical, Marxian, and Lewis dual sectors and then by pointing to the current distinction between formal and informal sectors with the consequences of the phenomenon of informality on measured unemployment. We consider the recent 21st Century experience during the Great Financial Crisis and the current COVID-19 crisis, which, we believe, opens the door to how Karl Polanyi’s vision can offer alternative policy perspectives. This is of crucial significance for those of us who wish to prevent a return to neoliberal policies during the future post-pandemic period, particularly in the emerging and developing countries, where the highest incidence of employment informality prevails.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".