〔紹介〕 G.B.Gorton, Misunderstanding Financial Crises: Why We Don’t See Them Coming, Oxford U.P., 2012.
Bibliographic record
Abstract
紹介 １、 「静穏期」の形成：州法銀行時代、国法銀 行時代、中央銀行と預金保険制 本書は、歴史的説明を州法銀行時代、1837-63 年、から始める。 この時期、額面等価保証の国家紙幣はなく、 金銀鋳貨とともに約 1500 種の私的銀行(state banks，private banks)が発行する銀行券が流通 媒体＝通貨として機能していた。そして、銀行 券発券保証準備には連邦債・州債の担保を要し、 額面での金銀正貨兌換に応ずべし、と定められ ていた。 しかし額面兌換(金銀貨兌換)は実施されず、 銀行券の通用力の額面割れ、ディスカウント、 は日常的で、 発券銀行リスクもさることながら、 発券銀行に赴く時間と距離の負担が大きかっ た。例えば、ニューヘブン
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".