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Record W829403228

Building Socialism From Below: Luxemburg, Sears, And The Case Of Occupy Wall Street

2014· article· en· W829403228 on OpenAlexaff
H. E. A. Campbell

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicUniversity Challenges and Reforms
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCapitalismSocialismVisionPoliticsPolitical economySocial movementSociologyDemocracyEquity (law)Environmental ethicsPolitical scienceNeoclassical economicsEconomicsLawCommunism
DOInot available

Abstract

fetched live from OpenAlex

For as long as capitalism has existed, people have struggled against it. However, despite the fact that anti-capitalist social movements have won important battles and at times created change, the global capitalist system remains largely intact, ever growing and expanding. How might waves of resistance help pave the way for a different economic and political system— one based upon the principles of accountability, equity, justice, and production for human need? This paper examines how anti-capitalist theories and writings, as well as a radically democratic social movement, can inform visions of a sustainable future that is productive, just, and built upon the needs and well-being of people: a future of socialism-from-below. After clarifying the political vision identified as socialism-from-below, I outline the contributions of two influential theorists in this tradition: Rosa Luxemburg and Alan Sears. I then apply their theories on the potential for social movements, and the characteristics of socialism-from-below, to the case of Occupy Wall Street. By applying the lessons learned through Occupy, future movements can meaningfully contribute to the long-term process of developing social movements with the capacity to resist capitalism in a more sustainable way.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0240.036
Scholarly communication0.0090.010
Open science0.0010.007
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.015
GPT teacher head0.246
Teacher spread0.231 · 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 designNot applicable
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

Citations0
Published2014
Admission routes1
Has abstractyes

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