Is This Time Different? Capture and Anti-Capture of U.S. Politics. The Economists’ Voice 9
Bibliographic record
Abstract
Societies are molded by their institutions that determine both their levels of prosperity and how that prosperity is distributed within society. For most of its history the United States has had economic institutions which have been inclusive in the sense that economic opportunities have been open to most, the playing field has been level, and property rights have been secure. The inclusiveness of economic institutions has meant that the United States has been fully able to harness the talent of its citizens who have consequently experienced high rates of social mobility. Take Thomas Edison, the inventor of the phonogram and the light bulb and the founder of General Electric, still one of the world's largest companies. Edison was the last of seven children. His father, Samuel Edison, followed many occupations from splitting shingles for roofs, to tailoring, to keeping a tavern. Thomas had little formal schooling but was home schooled by his mother. He was not an elite or well connected but the economic institutions of the US, like the patent law (he had a world record 1,093 patents issued to him in the US) allowed him to thrive to the benefit of himself and society. Sokoloff and Kahn (1990) showed that innovation, as measured by patenting, in the US in the 19 th century was driven by such non-elites. Obviously economic institutions were not inclusive everywhere in the US. The federal system allowed for institutional divergence within the US and the South had much more extractive institutions, with a tilted playing field in favor of elites and weak or absent property rights for many in society. The slave economy in the US South epitomizes the nature of extractive economic institutions. Instead of opening economic institutions to everyone or allowing social mobility, extractive institutions restrict opportunities to a powerful few and block social mobility. The children of slaves were also slaves, slaves could not own property, had no 1 The concepts and arguments used in this paper borrow heavily from our forthcoming book Acemoglu and
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".