Trade, Technology, and Transitions: Trampolines or Safety Nets for Displaced Workers?
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
In the past several decades, the developed world has experienced significant labour market dislocations caused by international trade, technology, and other factors. While economic nationalism has risen in response to these challenges, technology is typically a more important factor than trade as a cause of these dislocations. Further, trade-related responses often impose additional costs on consumers through higher prices and on downstream industries that utilize inputs from protected sectors. Thus, the article argues that effective use of labour market adjustment policies (LMAPs) is a preferable approach to protectionist policies in addressing labour market adjustment costs. After laying out a spectrum of passive and active labour market policies, the article then goes on to provide a comparative evaluation of LMAPs in the USA, Canada, select Nordic and continental countries in Europe, and Australia. The article’s comparative evaluation suggests that the Nordic model, Germany, and Australia provide the most compelling utilization of LMAPs, while the USA lags behind other countries in our sample in relative resources devoted to LMAPs. However, recent trends in these jurisdictions suggest some degree of convergence on an ‘activation’ paradigm that utilizes incentive reinforcement and benefit conditionality in triggering participation in active labour market programmes.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it