Bibliographic record
Abstract
Extract “This wide-ranging book offers a unique view of the economics behind technology, production, and industries. Its distinct perspective is engaging and sure to raise questions in readers’ minds.”Chad Syverson, Chicago Booth School of Business “Professor Dosi offers a thought-provoking analysis of innovative processes. Zooming in to examine microfoundations in individual and organizational behaviors and zooming out to explain technological evolution and industry dynamics, this Manual builds a comprehensive model of the capitalist system and its evolution. A must-read for any innovation scholar.”Sarah Kaplan, Rotman School of Management, University of Toronto “To many of us the development of contemporary economies is an enigma that is difficult to ascertain from what is often offered in mainstream economic models. But what are alternative conceptions? In this fascinating volume, Giovanni Dosi takes on the challenging but tremendously important task to produce a framework for understanding the economy as a complex evolving system characterized by heterogeneous agents and their bounded rationality. Written as an admirably comprehensive manual, it draws upon half a century of his seminal contributions to evolutionary theorizing on economic and technical change. I highly recommend it to everyone in search for a complete yet structured understanding of the dynamic economic realities involving individuals, organizations, sectors and the economy.”Frederik Tell, Uppsala University
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.575 | 0.421 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".