AASB Research Report: Connectivity of Non-Financial Information and Financial Information - A NFP Private Sector Study
Bibliographic record
Abstract
This research report investigates the connectivity between financial and non-financial information in the Australian not-for-profit (NFP) private sector, with a particular focus on the relevance and application of service performance reporting (SPR). The report draws on literature reviews, annual report analysis, surveys, and stakeholder focus groups to evaluate current reporting practices, stakeholder perceptions and practical pathways for improving integration, accessibility, and credibility of SPR across the sector. Key messages include:<br/>• Connectivity between financial and non-financial information remains fragmented across the NFP sector, with limited integration and inconsistent terminology.<br/>• Stakeholders (including donors, regulators, preparers, auditors, and directors) recognise the value of SPR but highlight challenges around implementation costs, capacity constraints, assurance gaps, and the need for flexible reporting guidance.<br/>• International case studies (e.g., New Zealand, United Kingdom, Canada) illustrate varied models of SPR, offering insights into balancing comparability, contextualisation, and proportionality.<br/>A successful SPR framework for Australia must be scalable, principles-based, and informed by stakeholder perspectives to ensure it is both credible and context-sensitive.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".