Journal of International Business and Economic Affairs
Bibliographic record
Abstract
Journal of International Business and Economic Affairs ISSN 1916-8748 (Online): Library & Archive Canada 1(1), 2024 Founder and Executive Director Ghada Gomaa A. Mohamed Editor-in-Chief Morrison Handley-Schachler Vice Editor-in-Chief Thomas Henschel Editorial Board (Alphabetically) Professors David Kirby Danial MayGhana Mohamed Hala El-RamlyIlka HeinzeJohn AdamsJyoti navare Manuch Irandoust Mohga Bassim Monal Abdel Baki Morrison H-Schcahler Mursed Chowdhury Omneya Abd-ElSalaam P. Malyadri Thomas Henschel Toumn El-Hamaki Yongsheng Guo Zainal Abu Zarim Shaleen Kumar Srivastava Updesh Khinda Editorial: Tahmid, Tahani, Sadia Binte Shafiq, Md. Yousuf, Peter Wanke, Md. Abul Kalam Azad. Are Women Gold-dust for Asian Banks? Examining the Impact of Gender Diversity on Asian Banks’ Performance and Risk Yakubu Musah Seidu Gender Discrimination in the Credit market of Sub- Sahara Africa; Does Firm Size Matter? https://epe.lac-bac.gc.ca/100/201/300/jrn_intl_business_econ_aff/2024/v01n01.pdf
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.274 | 0.184 |
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".