Bibliographic record
Abstract
millennium the precisions of Schumpeter and Lonergan and Kalecki regarding these functions and their control will be common talk, a common ethos.Random transfusions of government blood and the casinos of economic leeching will be identified, ridiculed, abhorred, in their unintelligent destructive ugliness. 1But we are not there yet.How can we get moving from leeches to economic science?What actions can we take to initiate the shift toward a time in the future when economists take the basic, surplus, and redistributive circuits for granted?This is the subject matter of Philip McShane's recent book Pastkeynes Pastmodern Economics: A Fresh Pragmatism.Pastkeynes Pastmodern Economics is Philip McShane's fourth major effort to generate serious interest in Bernard Lonergan's achievement in the field of economics.McShane's previous works include Lonergan's Challenge to the University and the Economy, Economics for Everyone, and Beyond Establishment Economics.Unfortunately, even with these books and Bernard Lonergan's two volumes, For A New Political Economy and Macrodynamic Analysis, Lonergan's challenge to the economy remains to be accepted.What, then, are the strategies on offer in Pastkeynes Pastmodern Economics that point towards economic science?
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.031 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".