The Popular Financial Reporting between Theory and Evidence
Bibliographic record
Abstract
The main international accounting associations have identified Popular Financial Reporting (PFR) as a decision-making tool to increase accountability and transparency as a possible decision lever coherent with the New Public Governance theory. The study has focused its attention on the features and contents of the PFR identified in the literature and present through the analysis of the 193 PFRs municipalities presented at the PFR Awards Program 2017. The analysis of the presence and absence of some characteristics confirms that the reality does not reflect the theoretical request, moreover the statistical analyzes carried out confirm various hypotheses related to the PFR but reject others such as the criterion of document length. The correlation between socio-economic characteristics of the population and the groupings of characteristics of each PFR. The study confirms a relationship between document length and level of education, and between percentage of non-native English-speaking residents and number of appaerance features. To the 23 observable criteria, additional possible ones are added which, based on logic and empirical evidence, will have to be studied to assess their impact in terms of transparency and accessibility.
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 | 0.020 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".