Bibliographic record
Abstract
With the slow recovery from the Global Economic Recession that began in 2008 and its lingering high unemployment in the United States and Europe, in spite of the best efforts of governments and central banks to remedy it, it may be helpful to suggest some adjustments in current economic thinking.One adjustment may be found in the introduction of National Economics, in addition to macro and micro-economic theory, to better engage issues of free trade, the international outsourcing of manufacturing and research and development known as globalization, protectionism, Chinese mercantilism, and national investment policies, which may accompany the preparation of economic stimulus packages.While free trade is generally acknowledged as a positive factor in contributing to economic growth, it has been used by mercantilists, both countries and corporations, as a cloak to achieve a National Income redistribution to enrich themselves at the expense of reducing employment, and wages and salaries within a country, and to substitute poorly made or low quality goods for goods of better quality. One issue of National Economics that stands to be addressed is the contribution of Chinese mercantilism to the Global Economic Recession and its effect on unemployment rates. A major trading partner with the United States, Europe, and other countries, China uses a substantially undervalued currency compared to the U.S. dollar to increase its export of manufactured goods and economic growth rate, while suppressing the manufacturing sector in its trading partners. Within many countries, large trade imbalances with China play a role in the distribution of National Income by depressing employment, wages, salaries, and investment. While mercantilists claim that these reductions in employment, wages, and salaries are offset by the proliferation of inexpensive Chinese goods, low quality goods do not compensate for reductions in employment and investment. A second issue of National Economics that stands to be addressed, at least within the United States, is the need to prepare economic stimulus packages that represent a balance of new spending along with adjustments in entitlement programs and a reworking of the current regulatory environment, which policymakers use to reward corporate dinosaurs and financial manipulators, while the constrict the ability of small banks and lending institutions such as credit unions to make consumer loans and finance mortgages, with the effect of repressing the nation's economy. Finally, some thoughts are given regarding the effect of Chinese mercantilism on Taiwan's economy, and Japan's effort to renew its economy.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.179 | 0.077 |
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".