Research Trends in Postmodernism: A Bibliometirc Analysis
Bibliographic record
Abstract
The aim of the study investigates the bibliometric data of Postmodernism gathered from the Scopus database. More to the point, it elucidates the overview of Postmodernism, in the midst of indication to the influence of advanced technologies, utility, significance and limitations of Postmodernism in all fields.The methodology part reflects on a a systematic evaluation of scientific articles in Scopus index journals particularly. From 1990 to 2021, the data acquired from Scopus database in sequence to attain the outcomes of the studies. The obtained and filter data are relevant to Boolean operators. Moreover, the software of VOSviewer is utilized to visually categorize and analyse the distribution of bibliometric data and network using of cluster maps.The findings of the study are categorized into three fractions: period of publication, coauthorship and citations. The result signifies that Postmodernism is trendy and unique around the world, and it has created a tremendous change in all the fields. It engages in recreation of the world. The study handles the articles only in the Scopus database, to expel journal articles as of additional databases like Web of Science, Dimensions, PubMed, etc. Additionally, English-literature gives the scope that the future researchers to explore in different languages related to work on Postmodernism will done. The implication of the present study draw attention to thebibliometric analysis via cluster maps fill the gap and results of previous study, in that way it provides accurate data to future researchers searching for their ways to build up Postmodernism and its trends. The current findings of the study accomplish the gap in the enlargement of a framework of comprehensive conceptual. It amalgamates the indication of Postmodernism in a single organization that left in previous studies.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.080 | 0.097 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".