Industrial policy imitation: the perils of matching the US Inflation Reduction Act to attract battery plants
Bibliographic record
Abstract
Implementation of the US IRA in 2022 significantly changed the practice of automotive-related industrial policy in the USA. We scrutinise its influence on a third country, Canada, where, in response to the IRA, more than CAD 42 billion has been committed to secure three battery plants with a value of CAD 19 billion. The purpose of our research is to determine if the incentive packages offered by the Canadian Government were truly necessary to secure the investments and if Canada can expect benefits comparable to those that similar support would engender in the USA, where the IRA was conceived. Based on our analysis, Canada's obligation to provide substantial incentives do not guarantee benefits on par with those of a core automotive country. Hence, as a semi-peripheral automotive nation, Canada's three new battery plants are unlikely to produce core country-like results, raising doubts about the effectiveness of Canada's strategy.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".