Collective Workers’ Funds and the Rise of Neoliberalism in Sweden and Québec
Bibliographic record
Abstract
Wage-earner funds (löntagarfonder) in Sweden and the Fonds de solidarité ftq in Québec, both founded in 1983, are two of the most significant examples of collective workers’ investment funds run by unions. This article situates the political context of their emergence in the neoliberal turn of social democracy in the early 1980s. In Sweden, the wage-earner funds were initially proposed as a radical anti-capitalist project in 1975, but the Social Democratic Party leadership developed the idea into a qualitatively distinct plan aimed at increasing investment capital available for private firms, as part of its new market-accommodating program. In Québec, the Fédération des travailleurs du Québec (ftq) proposed the solidarity fund as it moved toward concertation and away from the democratic economic planning and autogestion (worker self-management) that it had championed in the 1970s. In both cases, pro-market forces within organized labour proposed the funds so that workers’ capital could be used to stimulate private, for-profit investment, while recuperating elements of earlier labour radicalism that had sought to enhance workers’ power over capital. Built with an institutional orientation toward the incorporation of workers into financial capitalism, these collective workers’ funds represent a neoliberal shift within organized labour in Sweden and Québec, two places where labour is comparatively well organized.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".