Bibliographic record
Abstract
This article begins by pointing out, with regard to the study of stock market behaviour, the dangers of distortion inherent in factor analysis in principal components when applied as a method of grouping. As a follow-on to a preceeding contribution dealing with the period 1959-70 this article develops and clarifies the methodological aspects (dangers of factor analysis, utility of percolation method) within the context of the period 1974-79. The advantage of constituting groups from behaviourally homogenous markets, calculated according to the monthly variations in stock exchange rates of the 13 most important markets, is then analysed. The statistical analysis of links between national stock markets requires prudence as regards the use of notions in which the world stock markets are considered as being a whole, the concept of "economic blocks", indeed the same prudence must be exercised when considering the independence or interdependence of markets and the corresponding generalisations, although the long-term tendency would seem to have been modified since 1974 in a direction favourable to the empirical validation of the concept.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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; both teacher heads agree on what is shown here.
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".