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Record W1902573811 · doi:10.18740/s4d88c

Strategy, Meta-strategy and Anti-capitalist Activism: Rethinking Leninism by Re-reading Lenin

2009· article· en· W1902573811 on OpenAlexvenueno aff
Stephen D’Arcy

Bibliographic record

VenueSocialist studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceContext (archaeology)HumanitiesEthnologySociologyPhilosophyGeography

Abstract

fetched live from OpenAlex

Whereas Marxism is a theory, or rather a cluster of theories, Leninism is something else: a political strategy. And as Lenin himself pointed out, strategies are neither true nor false, but only effective or ineffective, depending largely on the context within which they are carried out. In the context of today’s North America, however, the adoption by radical activists of the standard Leninist norms for anti-capitalist organizing would be counter-productive. What is needed now is a very different approach: a strategy of attrition, as Lenin would have said, rather than a strategy of overthrow. This article concludes by sketching an attrition strategy for contemporary anti-capitalist activism. Tandis que le marxisme est une théorie, ou plutôt un agrégat de théories, le léninisme est autre chose: une stratégie politique. Et, comme Lénine lui-même l’a souligné, les stratégies sont ni vraies ni fausses, mais seulement efficaces ou pas efficaces, en fonction du contexte dans lequel elles sont mises en œuvre. Toutefois, dans le contexte de l’Amérique du Nord d’aujourd’hui, l’adoption par des activistes radicaux des normes léninistes habituelles pour des mobilisations anti-capitalistes serait contre-productive. Une approche très différente est désormais nécessaire: une stratégie d’usure, comme Lénine l’aurait dit, au lieu d’une stratégie de renversement. Cet article conclut en esquissant une stratégie d’usure pour l’activisme anti-capitaliste contemporain.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.149
GPT teacher head0.388
Teacher spread0.239 · 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 teacher head, not a consensus.

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

Citations1
Published2009
Admission routes1
Has abstractyes

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