A Use-Value Thesis on the Labour/Learning Process: Re-assessments and Expansion of Conceptual Resources
Bibliographic record
Abstract
Abstract: This article reviews a cross-section of theoretical resources dealing with skills, knowledge and work for their potential to further the analysis of previous findings of a Work and Lifelong Learning Research Network (WALL, Centre for the Study of Education and Work, University of Toronto) research project entitled Working IT: Learning new technology in the public sector1. This project, undertaken in partnership with the Canadian Union for Public Employees (CUPE), focused on changes that have affected social benefits delivery processes in Ontario (2002-2006). The article covers mainstream sociology of work literature and the development of Harry Braverman's labour process theory (LPT). Criticizing what is termed the 'up-skilling/de-skilling impasse', the review is followed by a discussion of several alternative conceptual resources that may help overcome this impasse and stimulate further development of LPT. In the end, a 'Use-Value Thesis' of the labour / learning process is outlined. This depends, first, on a rigorous and expansive understanding of the phenomena of skill, knowledge and human development, i.e. learning, in its own right; and second, on an expansive understanding of labour as not simply activity enmeshed within processes of capital accumulation but rather co-constitutive of the direct satisfaction of individual/collective human needs (i.e. use-value) as well. It is argued that recognizing 'use-value ' is central for addressing the contradictory interests and practices (e.g. up-skilling and de-skilling) that can occur simultaneously in workplaces, and for conceptualizing the inter-active role of a variety of social spheres.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.052 |
| Scholarly communication | 0.017 | 0.033 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".