Bibliographic record
Abstract
Abstract The American economist Irving Fisher (1867–1947) of Yale University introduced general equilibrium analysis into North American economics in his 1891 dissertation, and went on to become a leading monetary and capital theorist. The “Fisher equation” of his Appreciation and Interest (1896) viewed nominal interest as the sum of real interest and expected inflation (which he later modeled as a distributed lag of price changes). The “Fisher diagram” of The Rate of Interest (1907) showed optimal consumption and saving in a two‐period model, the basis of all subsequent analyses of intertemporal allocation. Fisher's The Purchasing Power of Money (1911) restated the quantity theory of money, with monetary shocks driving output fluctuations in the short run but affecting only nominal variables in the long run. His 1926 paper correlating unemployment and a distributed lag of inflation was reprinted in 1973 as “Lost and Found: I Discovered the Phillips Curve—Irving Fisher.” The “Fisher index”, the geometric mean of the Paasche and Laspeyres indexes, is now widely used as an index number. Emphasizing that inflation makes money and bonds risky, Fisher was an enthusiast for investment in common stocks in the 1920s. He shattered his public reputation with his October 1929 statement that stock prices had reached a permanently high plateau.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.042 |
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".