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Record W3121804783 · doi:10.22215/etd/2016-11686

Competition or Liberation? Implications of Labour Automation in the Context of Cognitive Capitalism

2016· dissertation· en· W3121804783 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

Venuenot available
Typedissertation
Languageen
FieldEnergy
TopicEnergy, Economy, and Technology Trends
Canadian institutionsCarleton University
Fundersnot available
KeywordsCapitalismContext (archaeology)Competition (biology)WageWork (physics)AutomationConstraint (computer-aided design)EconomicsEconomic systemPolitical economyLabour economicsPolitical scienceEngineeringPoliticsLawMechanical engineering

Abstract

fetched live from OpenAlex

Technology in the first half of 21st century are developing new abilities to perform autonomously and compete with humans directly in more and more tasks, opening up the future possibility of increasing labour substitution. Using the theory of Cognitive Capitalism to examine advanced economies as the most recent form of capitalism shows that in the modern economy work is increasingly central to the lives of individuals due to new cognitive labour which requires more worker engagement than industrial labour. This requirement has strengthened the direct coercive mechanisms of the increasingly precarious wage relationship and weakened alternate income sources. This dissertation argues that automation in this context could be harmful to individuals required to depend on work to survive and evaluates three policy options against the goal of freeing individuals from this institutional constraint to work so that they can continue to fully and freely participate in society if widespread automation occurs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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