The Political Economy of Technological Innovation and Employment
Bibliographic record
Abstract
Building on the varieties of capitalism thesis of comparative advantages in technological innovation, the authors theorize the effect of sociopolitical coordination from a dynamic perspective and then apply the dynamic theories to the political economy of employment, in comparison to the existing employment literature situated in a constant-technology context. Based on cross-sectional survey as well as pooled time-series aggregate data, the authors argue that new technologies not only increase productivity through process innovation but also generate rents through product innovation. By preventing opportunistic behavior between firms, sociopolitical coordination intensifies reciprocal sharing of innovation, which increases productivity returns but dilutes rents, leading to comparative advantage in process over product innovation. Because process innovation is labor saving but product innovation is employment friendly, interfirm coordination further leads to comparative disadvantage in job creation from innovation. In other words, the Anglo-Saxon employment creation advantage, currently identified on the static basis of noninnovative low-skill industries, is reinforced by a similar advantage from the dynamic perspective, based on strength in job-friendly innovation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".