Prolégomènes à toute appréciation critique de CANDIDE
Bibliographic record
Abstract
This text describes the CANDIDE model from three critical points of view. First, it presents the structure of the model with the aid of a table of "supersectors" and a flow chart. The discussion of the linkages between these supersectors brings out the general equilibrium character of the model. The center section of the paper deals with the theoretical foundations of the behavioural equations. A statement of the equation specification in each sector of the model is followed by a brief evaluation. The authors confess to an eclectic attitude and stress the practical difficulties of making stylized theories bring order in variegated facts. Exogenous influences on the model are discussed as well. The same eclectic approach is evident in the third part of the text which treats of estimation and validation. A variety of tests and checks—some novel ones included—are applied in the process of developing the model. The authors conclude with the observation that recent tumultuous developments in the economy raise fundamental questions about the validity and usefulness of models like CANDIDE.
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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".