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Record W2084136514 · doi:10.1017/s0003055402850249

Social Movements and Economic Transition: Markets and Distributive Conflict in Mexico. By Heather L. Williams. Cambridge: Cambridge University Press, 2001. 239p. $54.95.

2002· article· en· W2084136514 on OpenAlexaff
Judith Adler Hellman

Bibliographic record

VenueAmerican Political Science Review · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsYork University
Fundersnot available
KeywordsUnrestSocial unrestSocial movementDistributive propertyState (computer science)Political economyConstruct (python library)SociologySocial conflictPolitical scienceDevelopment economicsEconomic historyEconomicsPoliticsLaw

Abstract

fetched live from OpenAlex

Students of social movements have long struggled to explain why insurgencies occur where and when they do. In this excellent study, Heather Williams examines two contemporary Mexican movements—one rural, one urban—as a means to explain why unrest develops, when movements form, and what movement activists are likely to do once they manage to construct an organization and articulate a set of collective demands. Expanding on the work of Doug McAdam, Sidney Tarrow, Charles Tilly, and other scholars who have wrestled with these questions, Williams is concerned with the way in which Mexico's successive economic crises, and the implementation of neoliberal policies in response to these crises, influence the manner in which the dispossessed organize and press their demands on the state.

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)0.001
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0020.004
Scholarly communication0.0030.007
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0140.002

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 head0.021
GPT teacher head0.292
Teacher spread0.271 · 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
GenreOther

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
Published2002
Admission routes1
Has abstractyes

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