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Record W1581788861 · doi:10.7202/1024212ar

Learning in Struggle: Argentina’s New Worker Cooperatives as Transformative Learning Organizations

2014· article· en· W1581788861 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueRelations industrielles · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransformative learningCapitalismPoliticsSociologyBusinessPublic relationsPolitical science

Abstract

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This article considers Argentina’s empresas recuperadas por sus trabajadores (worker-recuperated enterprises, or ERTs) as transformative learning organizations . ERTs are illustrative of how workers’ conversions of capitalist firms into worker cooperatives—especially conversions emerging from troubled firms and in moments of deep socio-economic crises—transform workers (from managed employees to self-managed workers), work organizations (from capitalist businesses to labour-managed firms), and communities (from depleted to revitalized and self-provisioning localities). Theoretically, the study is grounded in class-struggle, workplace learning, and social action learning approaches. These theoretical perspectives help the study work through how workplace conversions by workers, when converting troubled investor-owned or proprietary firms into worker coops, act as catalysts for contesting workplace exploitation and capitalist crises, while also beginning to move beyond them by forging new social relations of production and exchange. In the case of Argentina’s ERTs, crises in the political economy and micro-economic crises at the point of production during the collapse of the neoliberal model at the turn of the millennium heightened workers’ self-awareness of their situations of exploitation and motivated collective action. As a result, new worker cooperatives were created that also stimulated the social, cultural, and economic renewal of surrounding communities. The study’s research method relies on extended case studies of four diverse ERTs, which included ethnographic observation and in-depth interviews. Observations of daily workflows were conducted, as well as interviews and informal conversations with founding and newer ERT workers. In a more structured portion of the interview protocol, key-informants were asked to reflect on how they had personally changed after being involved in the ERT, and how production practices and involvement with the community had transformed in the process of conversion. The article concludes by outlining how worker, organizational, and community transformations emerge from workers’ processes of informal learning and learning in struggle as they collectively strive to overcome macro- and micro-economic crises and learn to become cooperators. This learning, the study shows, occurs in two ways: intra-cooperatively via informal workplace learning, and inter-cooperatively between workers from different ERTs and with surrounding communities. The self-management forged by ERTs thus embodies new, cooperative, and community-centered values and practices for these workers that, in turn, sketch out different possibilities for economic and productive life in Argentina.

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.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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