(Professor) Hadrian’s Wall: The Role of the Australian Research Council in Research Security
Bibliographic record
Abstract
Research security is the action of protecting sensitive, classified or commercially valuable knowledge and technologies from espionage, theft, interference and illicit transfers. Yet academic explorations of research security are still at their most formative stages. This is especially the case in Australia and its universities, which has been accused in recent years of falling behind research security efforts compared to other Western nations such as the United States (‘US’), Canada, the United Kingdom and the European Union (‘EU’). This article has two purposes. The first is to highlight the important role that the Australian Research Council (‘ARC’) has played in providing Australian research security. The second purpose of this paper is to illustrate the significant undeveloped potential for the ARC. Drawing on examples from the funding bodies in the US and Canada (including recent changes to their enabling statutes and regulations), this article argues for an increased role for the ARC in securing the university research enterprise.
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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.010 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.018 | 0.026 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".