Knowledge and innovation in the interface between the steel and automotive industries: The case of Dofasco
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
Warrian, P. and Mulhern, C. (2005) Knowledge and innovation in the interface between the steel and automotive industries: the case of Dofasco, Regional Studies 39 , 161–170. The key motivation behind innovation in the steel industry has been the revolution in vehicle manufacturing, as automotive steel represents the largest source of revenue for integrated mills. The paper examines in a comparative context the innovative practices of North America's most profitable integrated automotive steel producer, Dofasco Inc. It seeks to elucidate conclusions from previous work on knowledge derived from participation in global learning networks. The authors claim that Dofasco is a commercialization‐stage innovator. It adds value to a product or process as it meets the market, but does not significantly contribute to fundamental and applied scientific research in automotive steel production. The geographic sphere in which most of Dofasco's customer‐oriented innovation occurs is in a regional system of innovation, specifically the automotive parts and assembly hub of south‐western Ontario and Michigan.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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