Bibliographic record
Abstract
Gazing down on the field of historical geography from a lofty vantage point, the most obvious conclusion one can draw is that it is alive and well. Despite gloomy forecasts in the 1980s (Wyckoff and Hausladen 1985), the number of significant titles published in recent years and the consistency of historical geographic scholarship testifies to the vitality of this subdiscipline. Johns Hopkins, along with Texas, California, Chicago, and other university presses have released handsome and important contributions. Recently, the second and third volumes of the highly regarded Historical Atlas of Canada (Harris and Mathews 1987–93) have appeared; and Thomas McIlwraith and Edward Muller (2001) have revised the standard 1980s text on North American historical geography. The Journal of Historical Geography has a healthy backlog of manuscripts; The Geographical Review regularly features work from specialty group members; and Historical Geography has grown in size and substance. Although the number of academic job listings for historical geography may never challenge the opportunities in GIS, a sizable and energetic corps of practitioners is hard at work, whatever their individual job titles. The decade that has elapsed since Earle et al.’s (1989) review of the field (see also Conzen, Rumney, and Wynn 1993) has been particularly productive for historical geographers in terms of theory and approach. Studies framed by colonialism, capitalist development, postmodernism, feminism, and environmental history are all inherently interdisciplinary and add to the complex intellectual current in which historical geography finds itself. This diversity poses a particular problem for the authors of a chapter with panoramic intent. Like a bird’seye view of a nineteenth-century city, the most prominent structures, or themes, stand out in the foreground. Common dwellings, or the vast body of supporting literature, blend into a less distinct background pattern. Outstanding singular efforts rise like spires above the cluttered landscape. This chapter hopes to call attention to the scholarship found both along the main thoroughfares and the back streets in the bird’s-eye view, while also pointing out unique contributions. Anne Mosher’s (1999) outline of several major trends in historical geography scholarship provides the framework for this chapter.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.091 | 0.024 |
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".