Economic Geography and the Financial Crisis: Full Steam Ahead?
Bibliographic record
Abstract
This article considers whether the growing theoretical and methodological diversity or pluralistic nature of economic geography contributes to its lack of engagement outside the discipline and academy. Although we are enthusiastic about the vibrancy this pluralism brings, we also speculate that it contributes to the discipline's tendency to fall short of significantly impacting key debates in the social sciences. In particular, we consider the disciplinary challenges to influencing mainstream debates over financialization and the recent financial crisis and the recurring lament that economic geography “misses the boat” by failing to significantly impact key scholarly and policy issues. Specifically, we suggest that methodological and theoretical diversity, local contextualization, and relational analysis, all of which we support as vital to the discipline, make it difficult to isolate a disciplinary core. We conclude that pluralism produces a vibrant discipline with unique explanatory power but that it also has important impacts on the design, execution, and influence of geographers’ research outside the discipline.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 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".