Bibliographic record
Abstract
The Independent Review of the Australian Public Service (the APS Review) is developing a program of transformational reform to ensure the APS is: apolitical and professional, agile, innovative and efficient – driving both policy and implementation through coherent, collaborative, whole-of-government approaches … [with] the capability to meet core responsibilities and deliver functions, and to understand and deploy technology and data to drive improvement. Achieving this vision involves questions about the purpose of the APS, what government does, and how it goes about doing it. It also involves looking to current and future states. Australia is not alone in exploring these questions; similar processes are underway in the United States of America, Canada, and New Zealand. These are being driven by the complex reality of governing and the realisation that we work in complex, interwoven systems where boundaries are fuzzy, and governments engage with many other actors to achieve outcomes. How to steward this more disarticulated state has become one of the most pressing questions facing governments. How we answer these questions, however, must be anchored in the experience and aspirations of all Australians. In this paper we explore how these questions relate to the practice of commissioning and contracting. And we consider how the APS of 2030 should deploy these tools in pursuing outcomes. We set out a vision for an APS that is more strategic and where a much wider range of tools are used to deliver on outcomes. An APS that has transitioned from a procurement mindset to adopting approaches that allow it to fully leverage the potential within the APS, and with those it works with. The APS will need access a fuller and more appropriate set of contracting tools, consider a broader set of relationships, and have the capability to design and steward complex systems, in pursuit of outcomes for all Australians. Our analysis points to a range of enduring and emerging challenges that demand attention. The future state we sketch out demands fundamental change. By starting this journey now, the APS can improve current practice and provide the foundations for bold new ways of working in the future.
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 | 0.025 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.034 |
| Scholarly communication | 0.023 | 0.034 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".