COMPARISON OF THE ACADEMIC PERSPECTIVES OF ACCOUNTING FACULTY MEMBERS IN UNIVERSITIES IN TURKEY AND AROUND THE WORLD
Bibliographic record
Abstract
The main objective of this study is to examine the profiles of accounting faculty members in the top 100 universities of the world which are ranked and published in the business management program by Quacquarelli Symonds QS organization, in terms of variables such as gender, title (rank), number of publications and citations; and to compare them with the profiles of accounting faculty members in Turkey. In order to make this comparison, universities in Turkey were divided into 4 groups: the oldest universities in Turkey, the best universities, foundation universities and newly established universities, and 10 universities were selected from each group. Thus, the closest and furthest groups to the faculty member profile in the best universities in the world would be identified and the general profile of the faculty members in Turkey would be revealed. One result to the study reveals that the average number of accounting faculty members in the best universities around the world and the number of academic studies and citations of these academicians constitute a larger number compared to Turkey.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".