Yellow Pages Global Entrepreneurship Monitor Australia 2000
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
The Global Entrepreneurship Monitor (GEM) refers to both a set of linked, international research projects and a set of documents that reports project results. Each year, a number of countries (10 last year, 21 this year and growing) perform related entrepreneurship research using identical methods. They each produce an independent report (GEM Australia, GEM USA, GEM Japan et cetera) which explores in considerable detail the nature, extent and effects of entrepreneurship within their individual country, including selected comparisons with other nations. Additionally, one international, coordinating document (the GEM Executive Report) is produced. It summarises each nation’s findings and discusses them at the level of international generality. GEM was conceived in September 1997 as a joint research initiative by Babson College (USA) and London Business School. It went ‘into the field’ for the first time last year. The central aim was, and is, to bring together the world's best scholars in entrepreneurship to study the complex relationship between entrepreneurship and economic growth. From the outset, the project was designed to be a long-term multinational enterprise. In order to obtain reliable, comparable data, GEM originally focused on the G7 countries (Canada, France, Germany, Italy, Japan, United Kingdom (UK) and USA), with three additional countries (Denmark, Finland and Israel) added because of the availability of scholars in these countries with particularly relevant expertise. GEM 2000 extends coverage to 21 countries in total. The additions are Argentina, Australia, Belgium, Brazil, India, Ireland, Norway, Singapore, Spain, South Korea and Sweden. Eventually, it is envisaged 40 to 50 countries will be included.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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