Web hyperlink patterns and the financial variables of the global banking industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The goal of the study is to explore business and social information contained in web data and to examine the effectiveness of webometrics methods in obtaining this type of information. Specifically, this study combines the inlink and co-link analysis techniques to make a complete examination of the international banking industry. Results from the analysis were compared with the banks’ real financial situation to determine the validity and reliability of the link analysis methods. Statistically significant correlations were found between inlink data and several financial variables. A comparison between Asian banks and other banks showed that the former attracted significantly more inlinks. The multidimensional scaling (MDS) maps generated from co-link data suggest that geographic and linguistic factors determine competitive clusters in the international banking industry. A comparison of the MDS maps from the two different time periods revealed important business information, notably that the Chinese banks moved closer to the major banks from the USA and UK.
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.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.006 |
| Open science | 0.002 | 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 it