The labour process: individual learning, work and productivity
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.
Bibliographic record
Abstract
Click to increase image sizeClick to decrease image size Notes 1. An earlier version was presented at the Future of Lifelong Learning and Work conference, OISE/UT, in June 2005. We acknowledge the suggestions of three anonymous reviewers. 2. The notion of ‘recurrent education’ (OECD, Citation1973; Edding, Citation1979) is a temporal reorganization of formal learning opportunities, which recognizes that a right to formal education can be earned by working for the community. 3. The EJRM project has been funded by the Social Sciences and Humanities Research Council of Canada. Information on this project is available at the CSEW Website (www.oise.utoronto.ca/csew). We thank Meredith Lordan, Sandia Officer, Marion Radsma, Johanna Weststar and Olivia Wilson of CSEW, who carried out the case study interviews. 4. Decisions to act or to abstain from action are no different in principle. 5. Average hours of estimated total informal learning and of job-related learning, respectively. 6. Polanyi's term ‘tacit knowledge’ should be extended to include abilities. 7. Polanyi used the term ‘skill’ but this word lacks agreed definition, and in common usage refers either to a particular attribute or to a level of education.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it