A bibliometric analysis of a national Journal: The case of the Turkish Journal of Psychology
Bibliographic record
Abstract
ttempt to answer this question, this study conducts a bibliometric analysis of the Turkish Journal of Psychology (Turk Psikoloji Dergisi [TPD]) as indexed in the Social Science Citation Index Multidisciplinary Psychology since 1995, volume 10, issue 35. Descriptive data showed that TPD published a total of 215 articles, about 11 per year, in Turkish (84.65%) and English (15.35%). On an average, an article was authored by 2 (2.01) authors and the article/unique author ratio was about 1:1 (.98). Apart from Turkey, authors were affiliated with the USA, Canada, The Netherlands, Australia, Cyprus, England, and Germany. Most of the publications were products of authors affiliated with universities in Ankara, Turkey. TPD was ranked 115 out of 126 journals in the category of Multidisciplinary Psychology in the Journal Citation Reports‑Social Sciences Edition, with an impact factor of 0.214 in 2012 and a 5‑year impact factor of 0.154. Aside from the most common words such as the, in, and so on, “Turkish” (n = 30), followed by “study” and “memory,” were the most frequently used words in titles; “study,” (n = 325) “memory,” (n = 206) and “between” (n = 201) were the most frequently used words in abstracts. On an average, articles had about five keywords, including about four keywords unique to the article. These findings suggest that TPD is an extremely local, but highly impactful journal publishing articles on very diverse topics from self to culture, and from memory to depression to scale development.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.027 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.233 | 0.518 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".