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Record W4309907949 · doi:10.1111/japp.12631

Work, Justice, and Collective Capital Institutions: Revisiting Rudolf Meidner and the Case for <scp>Wage‐Earner</scp> Funds

2022· article· en· W4309907949 on OpenAlexfundno aff
Markus Furendal, Martin O’Neill

Bibliographic record

VenueJournal of Applied Philosophy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsnot available
FundersMarcus och Amalia Wallenbergs minnesfondUniversidade do MinhoUniversity of OxfordConcordia UniversityBritish AcademyUniversitat Pompeu FabraIndependent Social Research Foundation
KeywordsCapital (architecture)DemocracyWageEconomic JusticePower (physics)PoliticsEconomicsEconomic democracyProperty rightsPolitical economyLaw and economicsPolitical scienceMarket economyNeoclassical economicsLawMicroeconomics

Abstract

fetched live from OpenAlex

ABSTRACT This article makes the case for a specific variety of what we call Collective Capital Institutions (CCIs), by returning to the idea of Wage‐Earner Funds (WEFs) – a 1970s Swedish policy proposal designed gradually to shift ownership and control over parts of the economy to democratically controlled institutions. We identify two attractive rationales in favour of such a scheme and argue that both can fruitfully be transposed to the current worldwide economic situation. The egalitarian rationale is that WEFs could help in the pursuit of equality by giving a wider set of people a stake in collectively owned companies and a right to their profits. The democratic rationale is that WEFs redistribute not only these profits, but also the power over economic decisions made within companies. We then contrast such schemes for collective capital ownership with the similar but much more privatised proposals set out in, for instance, John Rawls's idea of a ‘property‐owning democracy’. We argue that CCIs ultimately are more likely to contribute to the development of the ‘sense of justice’ within society that is needed for a stable just society. We conclude that CCIs deserve a great deal more exploration in academic and political discussions of egalitarian economic systems.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.063
Scholarly communication0.0100.009
Open science0.0020.006
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.042
GPT teacher head0.291
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2022
Admission routes1
Has abstractyes

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