Bibliometric analysis using R on corporate governance mechanisms / Hamizah Hassan
Bibliographic record
Abstract
This research intended to shed light on existing and future research trends of corporate governance mechanisms by offering a full bibliometric mapping through descriptive and network analyses of corporate governance studies. The multi-perspective research articles on corporate governance mechanisms, spanning from 1996 to the third quarter of 2022, were identified and analysed using Biblioshiny, a Bibliometrix R software. Prior to the analysis, the selected articles were scanned, cleaned, and harmonised. Overall, findings from this bibliometric study provided important information on current and future corporate governance publications. This included information on highly cited documents, most productive contributors, most frequently used keywords, most productive countries and sources, network analysis data on co-occurrence networks, and themes mapping information on corporate governance mechanisms studies. The Scopus database was used as the search strategy to find relevant literature. As an implication, this study provides useful findings to guide other researchers in mapping current and future studies on corporate governance mechanisms. To the researcher’s knowledge, this is the first Biblioshiny-based bibliometric analysis conducted on corporate governance mechanisms, with 282 documents analysed. The review emphasises on annual publication trends, the most productive authors, publications, countries, institutions, and sources, leading to future research priorities.
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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 | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.049 | 0.284 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".