Bibliographic record
Abstract
Using a cross-section of Nasdaq-listed Israeli companies, we examine the impact of R & D spending on their market values and the ecosystem for start-ups in Israel. We find a very strong positive association between the two, learning that $1 million of spending in R & D associated with an increase of $5 million of market value. Among all countries outside the U.S., Israel is third after Canada and China in terms of the number of stocks registered on Nasdaq. Since 1981, sixty-one companies have registered, and their total R & D spending in 2009 reached $3.750 billion, which is approximately equal to the total R & D expenditure of Turkey. In the region, Middle Eastern and North African (MENA) countries cannot accomplish to register in Nasdaq. Israel’s great success comes from the strong dedication and cooperation between private and public sectors in research and venture capital. Israel spends 4.7% of its GDP for R & D, which is equal to the total expenditure of MENA.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".