Expert paper #7, TPPA: Intellectual property and information technology
Bibliographic record
Abstract
Negotiations for the Trans-Pacific Partnership Agreement (TPPA) among twelve negotiating countries – Australia, Brunei Darussalam, Canada, Chile, Japan, Malaysia, Mexico, New Zealand, Peru, Singapore, United States and Vietnam – were concluded in Atlanta, USA on 5 October 2015. The text was released on 5 November 2015. The agreement has 30 chapters and many annexes, with parties also adopting bilateral side-letters. The TPPA was signed on 4 February 2016 in New Zealand, which is the formal depositary. Each party to the negotiations must complete its own constitutional processes and requirements before it can take steps to adopt the agreement. The TPPA will come into force within two years if all original signatories notify that they have completed their domestic processes, or after two years and three months if at least six of them, including the US and Japan and several other large countries, have done so. This research paper is part of a series of expert peer-reviewed analyses of different aspects of the text.
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 | 0.015 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.014 | 0.006 |
| Insufficient payload (model declined to judge) | 0.082 | 0.033 |
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".