Bibliographic record
Abstract
Economics and Business Letters (EBL) came into being at the turn of 2011 with the aim of providing a modern outlet for high quality research in the fields of Economics and Business.The main distinctive feature of EBL was the opportunity of high speed publication with a global reach.Our strategy for achieving these goals relied on using a free-of-charge open source platform and on reducing revision cycles as much as possible while assuring an appropriate selection of quality contributions.Today we are proud to present the first issue of the second volume of the journal, which means that our editorial venture has survived its first year.As shown in the 2012 Activity Report, we received a large number of originals (82), which is indicative of the acceptance in the academic community of the journal during its first year of life.The rejection rate was relatively high (67%).This may have been due in part to our editorial policy of excluding major revision as an option in the review process.This policy, in turn, facilitated what we consider an impressively low average time of just 40 days to the initial editorial decision, which substantially contributed to speedy publication cycles.Three regular issues plus a special issue were published in 2012, comprising a total of 22 original papers.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".