Bibliographic record
Abstract
Abstract Accounting and Finance has evolved from a news bulletin to a full‐grown refereed academic journal that has published papers written by authors from Australia, New Zealand, the United States of America, Canada, Europe and Asia. The Journal published its 41st volume in 2001 and that anniversary issue coincides with the beginning of the new millennium. As part of the celebration of this important milestone, this article reviews the Journal's evolution, the variety of papers published and the Journal's impact on accounting and finance research in the Asia Pacific region. Data for 394 papers published in the Journal by 570 authors are analysed. I find that the distribution of institutions and authors that have published in the Journal is highly skewed, with the top five (11) institutions accounting for 35 per cent (51 per cent) of the published papers in the Journal. Similarly, 8 per cent of the authors have published 26 per cent of the articles in the Journal. Analysis of the citation pattern indicates that Accounting and Finance does not have much impact on research published in the Asia Pacific region, with the Journal accounting for only 1.06 per cent of all citations in the selected Asia Pacific journals. Sub‐period analysis indicates that not even the establishment of the editorial board in the latter half of the 1990s has helped improve the impact of the Journal on research published in the Asia Pacific region. However, compared with other Asia‐Pacific journals, Accounting and Finance has the strongest impact on publications in the selected journals. The impact is even stronger in the latter half of the 1990s. Also, the impact of Accounting and Finance on the more recent journals in the Asia Pacific region is stronger than that of the other more established journals.
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 | 0.035 | 0.122 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.025 | 0.025 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".