OECD model tax convention on income and on capital : condensed version, 2005 : and key tax features of member countries
Bibliographic record
Abstract
OECD Model Tax Convention on Income and on Capital (2005 Condensed Version) and Key Tax Features of the Member countries . TABLE OF CONTENTS. Model Tax Convention on Income and on Capital .Introduction . Model Tax Convention on Income and on Capital . Commentaries on the Articles of the Model Tax .Convention .Commentary on Article 1 Commentary on Article 2 Commentary on Article 3 Commentary on Article 4 .Commentary on Article 5 .Commentary on Article 6 .Commentary on Article 7 .Commentary on Article 8 .Commentary on Article 9 .Commentary on Article 10 . Commentary on Article 11 .Commentary on Article 12. Commentary on Article 13 . Commentary on Article 14 . Commentary on Article 15. Commentary on Article 16 .Commentary on Article 17 Commentary on Article .18 Commentary on Article 19 . Commentary on Article 20 .NonMember countries' positions . Annex. Recommendation of the OECD Council Key Tax Features of Member countries .Introduction. Australia , Austria , Belgium , Canada ,Czech Republic, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Japan, Korea (Rep.), Luxembourg , Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak, Republic, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States,
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.022 |
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".