Information‐theoretic model of induced technical change: Theory and empirics
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The paper develops an information‐theoretic model of induced technical change where payoff‐maximizing agents are exposed to a positive degree of uncertainty when adopting new technology due to unobserved cost factors. The derived equilibrium of the model comes in the form of a non‐degenerate probability distribution that defines the distance of productivity growth from the potential maximum growth on the innovation possibilities frontier, often called the technical inefficiency function (TIF) in the frontier estimation literature. Many forms of the TIF are shown to be derived by specifying a particular functional form of the payoff function in our model. The paper estimates the innovation possibilities frontier and the TIF using the KLEMS data for 1995–2015 and documents the time evolution and sectoral heterogeneity of the innovation possibilities frontier.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it