Elinor Ostrom's Legacy: Governing the Commons and the Rational Choice Controversy
Bibliographic record
Abstract
Elinor Ostrom had a profound impact on development studies through her work on public choice, institutionalism and the commons. In 2009, she became the first — and so far, only — woman to win a Nobel Prize for Economics (a prize shared with Oliver Williamson). Moreover, she won this award as a political scientist, which caused controversy among some economists. She committed her professional life to expanding traditional economic thinking beyond questions of individualistic rational behaviour towards a greater understanding of self-regulating cooperative action within public policy. In particular, she organized the University of Indiana’s Workshop in Political Theory and Policy Analysis with her husband, Vincent Ostrom, and the International Association for the Study of the Commons (IASC). She also earned the reputation of a loyal and caring colleague and mentor. She donated much money to the University of Indiana, including her Nobel Prize money. The purpose of this article is to identify and discuss Elinor Ostrom’s legacy in international development. Rather than being a simple obituary, this article also seeks to review the tensions arising from her work, especially concerning the debate about institutions and the commons, and particularly Ostrom’s own focus on rational choice theory and methodological individualism as a means of understanding cooperative behavior. Ostrom’s work here has defined a field of research, and radically changed understandings. It also inspired work on the governance of public economics (Ostrom et al., 1993), and later writings on the institutions of development aid (Gibson et al., 2005). By so doing, we argue that Ostrom’s main legacy within development studies has been her development and communication of rational choice approaches to institutional thinking. In turn, this work has influenced policy debates about natural-resource management, and recent approaches to multi-level governance and polycentrism within environment and development. Yet, this approach has also produced tensions within development studies, which remain largely unresolved (Bardhan and Ray, 2008a). We argue that Ostrom’s work reflected wider transitions in social science and international development over a period of decades, but also indicates some of the key dilemmas faced by development studies in integrating political science and economics as useful and respected forms of analysis.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".