The New Progressivism and its implications for institutional theories of development
Bibliographic record
Abstract
Abstract Context A growing body of literature argues that the world is better off now than it ever has been and that things will only get better. This trend, long identified in advanced economies, has more recently manifest in low‐ and middle‐income countries and is attributed to the rapid diffusion of technological innovation through global trade, investment, communications, research and educational networks. Purpose We label this literature “New Progressivism”, mapping its main claims and examining its limitations. New Progressivists pay insufficient attention to the interaction between technological innovation and institutional capacity. More specifically, we show that the New Progressivists fail to explain existing patterns of stagnation and regression, and suggest a modified approach. Approach and Methods Accounting for the significance of institutional pre‐ and co‐requisites in facilitating the uptake of innovation, we analyze the different interactions between technological innovations and institutional capacities. We then provide illustrative examples of these relationships drawn from the areas of health, education, and financial development. Findings Technological innovation has vastly improved human well‐being in many countries in recent decades, but understanding why innovation had been adopted in some jurisdictions but not others and why it has not always proven beneficial if adopted requires an account of jurisdiction‐specific institutional landscapes. Policy Implications In many contexts technological innovations will not achieve their full potential without attention being paid to their institutional pre‐ or co‐requisites. Technological innovation, by itself, provides no easy escape from the often admittedly daunting challenge of reforming dysfunctional institutions in low‐ and middle‐income countries.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.047 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".