Meeting The Increasing Need For Internationally Trained Engineers: A Review Of Technical Japanese Training In The U.S.
Bibliographic record
Abstract
Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract ‘1 _ —-.. . ..—. Session 2260 : —. . . ..- Meeting the Increasing Need for Internationally Trained Engineers: A Review of Technical Japanese Training in the U.S. Michio Tsutsui University of Washington 1. Introduction: the U.S.-Japan Technological Exchange and the Need for Japanese-proficient Technologists As the worfi becomes a borderless economy, technological exchange is rapidly increasing among nations, including the exchanges of technical information, technology, and technical specialists. Thus, it is essential for a country to make international exchange as efficient and effective as possible. In this regard, it is particularly important and urgent for the U.S. to improve its ways of importing technical information and technology from Japan and its ways of exporting U.S. products and technology to Japan. To clarify this point, let us examine some statistics concerning technological exchange between the two countries. (1) High tech product trade First, let us look at some statistics concerning the trade of high tech products between the U.S. and Japan. As can be seen in Table 1, the U.S. has been the largest buyer of Japan’s high tech products for years. 1 Statistics also show that Japan, in turn, has been the second largest purchaser of U.S. exports (next to Canada), buying $52 billion worth of goods in 1994. Among these purchases, manufacturing goods account for 60%. This 2 includes computers, ICS, aircraft, engines, and measuring and medical equipment. It is evident from these statistics that the U.S. and Japan are heavily dependent on each other for high tech product trade. Table 1 Exports of High Tech Products from Japan ( 1993) Products Total to us Ratio (million dollars) (%) Electronic Data Processing 16,885 9,270 54.9 Electronic DP Parts & 9,357 4,400 47.0 Accessories Communication 8,119 2,622 32.3 Semiconductors & ICs 15,385 4,573 29.7 Aircraft and Parts 598 492 82.3 (Source: Japan Ministry of International Trade and Industry) (2) Japan’s position in the technological world Next, let us examine Japan’s position in the world in terms of its technological strength. One thing we can look at for this purpose is Japan’s share of high tech product exports in the world. According to the Japan Science and Technology Agency, Japan’s share in the exporting of high tech products in the world surpassed 3 West Germany’s in 1981 and the U.S.’s in 1983. Table 2 shows the figures for 1992. $iiiiiii’ F 1996 ASEE Annual Conference Proceedings ‘.,JR13>:
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".