<i>Gender, Growth and Trade: The Miracle Economies of the Postwar Years</i>. By David Kucera. London: Routledge, 2001. Pp. xi, 217.
Bibliographic record
Abstract
The central theme of this book is the interplay of women's employment and the macro-economy in postwar Germany and Japan. David Kucera introduces the distinction between two possible types of flexibility in the labor market. The first occurs in the absence of interference with the market mechanism from laws or institutions. This flexibility may reduce unemployment and increase the response time to shocks, at the cost of low wages and insufficient training. In the second type of flexibility, a buffer group provides this flexibility, while core workers are protected from the vagaries of the market and receive training and high wages. Kucera argues that by using women as a buffer group to protect men, Japan is able at a macro-level to reap the benefits of both the “low-road” and “high-road” approaches. Bolstering this argument, and showing that Germany pursues instead the simpler “high-road” strategy, is the most important aim of the book.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".