Bibliographic record
Abstract
It has already been mentioned that in the mid-1930s, 7 out of 19 clearing agreements concluded by Germany were with Central and Southeastern Europe countries. These countries were either born as a consequence of the redrawing of the map of Europe after the First World War or had become independent of the Ottoman Empire in an earlier time, and they all had suffered badly during that war. After the war, international stabilization loans were extended under the auspices of the League of Nations in order to sustain their economies, stabilize their currencies, and, in some cases, help with the settlement of refugees following the huge dislocation of peoples. Equivalent to £80m (around $380m) in total, these loans were granted between 1923 and 1928 to Austria, Bulgaria, Greece and Hungary, in addition to the Free City of Danzig and Estonia. But these countries were hit by the international banking crisis that erupted in Central Europe in 1931; furthermore, the Depression contributed to a huge fall in the prices of agricultural products, the export of which was their main source of foreign exchange — particularly for the countries of Southeastern Europe. Their antiquated methods of production made their agriculture prey to American competition. In Western Europe, French self-sufficiency and the British Imperial Preference agreed upon in Ottawa in 1932 (which privileged trade with Commonwealth countries) closed two major markets to Balkan exports.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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".