Reinterpreting the Motor Car Analogy in Bernard Lonergan’s "For a New Political Economy"
Bibliographic record
Abstract
Economics as a discipline and as a social science and practice is very hard work to practice well. Many economists are in fact very conscientious in their practice. My own approach to the critique and study of economics has been based, at least in part, upon an adaptation of the Socratic method from the history of philosophy which, in the first instance, can be read as negative, critical, and skeptical. This aspect of philosophy quickly appealed to my desire for independent thinking as a young student, especially in its capacity to expose the ignorance of those who presented themselves as authoritative experts, … to expose what the expert does not know and even further where there may be the pretense of knowledge when in fact there is none. This of course doesn’t mean, in the Socratic tradition, that the critical philosopher or incisive skeptic has more knowledge, but rather he/she may only be discovering the ‘holes’ in the expert’s knowledge without necessarily knowing what might fill that hole. This, as in the story of Socrates, can lead fatefully to serious trouble with the powers that be in any institution or society. This certainly can be the case when from a philosophical perspective one proceeds to criticize the limitations of a venerable and admittedly powerful discipline such as economics.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".