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Record W4381106964 · doi:10.1080/21598282.2023.2207447

“Through Pluripolarity to Socialism: A Manifesto” One Year On

2023· article· en· W4381106964 on OpenAlexaff
Radhika Desai, Enfu Cheng, John Ross, Carlos Ron, Jenny Clegg, Ajamu Baraka, Keith Bennett, Олег Николаевич Барабанов, Gabriel Rockhill, Sara Flounders, Alan Freeman, Carlos Martinez, Ben Norton

Bibliographic record

VenueInternational Critical Thought · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicRussia and Soviet political economy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsManifestoSocialismCapitalismPolitical scienceCommunismChinaEconomic historyWorld War IIHumanityPolitical economySociologyHistoryLawPolitics

Abstract

fetched live from OpenAlex

The International Manifesto Group launched its manifesto, “Through Pluripolarity to Socialism” on 5 September 2021. Then, the world’s attention was riveted to the US’s ignominious exit from Afghanistan. The following speeches, delivered at the webinar to mark the first anniversary of the event, reflect on the tumultuous events of the year since, dominated by the US-led war on Russia, using Ukraine as a proxy, its wider international reverberations which have underlined as well as accelerated the US’s decline and declining international influence and by the very real prospect that a similar US-led war is being planned against China using Taiwan region as a proxy. The speeches below find that, though the Manifesto’s text was finalised before anyone could have imagined such wars, its general line pointing to the decline of capitalism and imperialism and the imperative for humanity to progress through pluripolarity—a world of variety of national economic formations that will inevitably result as efforts to build productive and egalitarian societies are undertaken—to socialism as capitalism’s ability to deliver anything remotely similar is manifestly exhausted, has been vindicated.

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)0.004
metaresearch head score (Gemma)0.004
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: Commentary · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.013
Scholarly communication0.0100.004
Open science0.0000.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.088
GPT teacher head0.419
Teacher spread0.331 · 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
GenreCommentary

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
Published2023
Admission routes1
Has abstractyes

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