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Record W2265080764 · doi:10.3167/latiss.2015.080202

'Our Table Factory, Inc.': Learning Marx through role play

2015· article· en· W2265080764 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.

Bibliographic record

VenueLearning and Teaching · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methodologies in Social Sciences
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsCapitalismProletariatSociologySurplus valueAlienationCommodificationBourgeoisieCommunismMarxist philosophyCapital (architecture)Social capitalSocial scienceNeoclassical economicsEconomicsEconomyLawPoliticsPolitical science

Abstract

fetched live from OpenAlex

Marx's critique of capitalism remains foundational to the university social science curriculum yet little is known about how instructors teach Marx. In post-industrial, service-oriented economies, students are also increasingly disconnected from the conditions of industrial capitalism that animate Marx's analysis. Inspired by the discussion of how a piece of wood becomes a table in Marx's Capital Vol. 1., 'Our Table Factory, Inc.' simulates a diverse array of roles in the chain of production into and out of a table factory to understand key concepts: means/mode of production, use/exchange value, primitive accumulation wage/surplus labour, proletariat, bourgeoisie, alienation, false consciousness, commodity fetishism and communist revolution. We describe the exercise and present qualitative and quantitative assessment data from introductory sociology undergraduates across three small teaching-intensive universities in the United States. Findings detail the exercise's efficacy in fostering retention of material and in facilitating critical engagement with issues of inequality.

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)0.014
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.134
GPT teacher head0.424
Teacher spread0.291 · 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