Bibliographic record
Abstract
This article is based on a presentation given at a seminar 'Current Foreign Direct Investment (FDI) Trends and Investment Agreements: Challenges and Opportunities'. This seminar was organised by the Ministry of Foreign Affairs of Chile and sponsored by the Governments of Canada and Japan, as a co-operative initiative on international investment among the Asia Pacific Economic Cooperation (APEC) Investment Experts Group and the Investment Committee of the Organisation for Economic Cooperation and Development (OECD) Directorate for Financial and Enterprises Affairs in May 2004. It discusses the growing trend for international organisations and individual countries to incorporate transparency standards into IIAs. Transparency is generally viewed as an important element of good public and private sector governance. It also figures prominently among investors' concerns and has been embraced by APEC and OECD as a key liberalisation principle. In October 2003 both organisations announced new steps towards the implementation of more transparent legal regimes. These initiatives show a remarkable degree of convergence on the economic benefits and the means for achieving regulatory transparency.
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 | 0.035 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.016 | 0.016 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".