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
Today, the positive impact of entrepreneurship in the economy has been globally accepted. Entrepreneurs could provide efficient techniques to face with upcoming economic challenges. In this paper, we first investigate the effect of entrepreneurship on growth of economy over the period 2005-2011. Then we study the impact of four factors including Gross domestic product per worker, Growth in capital per worker, New firm creation and Technological innovation intensity on economic growth. The proposed model of this paper uses ordinary least square technique to investigate the relationship between four independent variables and economic growth. The results show that gross domestic product per worker is the only variable, which is statistically meaningful when the level of significance is five percent and the impact of other three variables including growth in capital per worker, new firm creation and technological innovation intensity are not statistically meaningful. In other word, as we see a 1% increase in gross domestic product per worker we could expect 8.712% increase in economic growth.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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