Bradford’s Law in the Field of Psychology Research in India
Bibliographic record
Abstract
The main objective of this investigation is to know the applicability of Bradford’s law in Psychology research in India. A total of global wise 14,30,700 papers has be published and 12,543 (0.88%) with 96,871 published in India than retrieved from the “Web of Science” citation database for a time of twenty years i.e. from 2001 to 2020. The study examined the countries wise research output, communication channels preferred by the researchers, and most productive journals in Psychology literature. The analysis of the study revealed that there is an increasing trend in terms of research productivity during the period. USA 5,11,528 (35.75%) Psychology research publications followed by England with 1,32,460 (9.26%) Germany96,620 (6.75%), Canada country 75,238 (5.26%), China and Spain both countries 2.49% research paper published and seven and eight stage ranked and India country psychology research papers published with 12,543 (0.88%) eighteenth ranked. The maximum number of research papers are published by Indian Journal of Psychiatry 4,316 (34.49%) and 3,909 (4.04%) citations first ranked followed by Asian Journal of Psychiatry 772 (6.17%) papers, 2,835 citations. The percentage of the error is negative and negligible (-0.00870), therefore the data conforms well fit to Bradford’s law zone.
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 | 0.002 | 0.000 |
| 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 | 0.000 | 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".