Reopke Lecture in Economic Geography: Notes from the Underground: Why the History of Economic Geography Matters: The Case of Central Place Theory
Bibliographic record
Abstract
abstract The discipline of Anglo‐American economic geography seems to care little about its history. Its practitioners tend toward the “just do it” school of scholarship, in which a concern with the present moment in economic geography subordinates all else. In contrast, I argue that it is vital to know economic geography's history. Historical knowledge of our discipline enables us to realize that we are frequently “slaves of some defunct” economic geographer; that we cannot escape our geography and history, which seep into the very pores of the ideas that we profess; and that the full connotations of economic geographic ideas are sometimes purposively hidden, secret even, revealed only later by investigative historical scholarship. My antidote: “notes from the underground,” which means a history of economic geography that delves below the reported surface. This history is often subversive, contradicting conventional depictions; it is antirationalist, querying universal (timeless) foundations; it seeks out deliberately hidden and buried economic geographic practices, relying on sources literally found underground—personal papers and correspondence stored in one subterranean archive or another. To exemplify the importance of notes from the underground, I present an extended case study—the 20th‐century development of central place theory, associated with two economic geographers: the German, Walter Christaller (1893–1969), and the American, Edward L. Ullman (1912–76).
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".