Past‐president's address: is geography (the discipline) sustainable without geography (the subject)?
Bibliographic record
Abstract
We commonly define geography as the ‘integrative’ discipline, but there is more rhetoric than reality in the notion that our discipline has a coherent view of the world. Academic geography is dominated by increasingly esoteric topical specialties, and too often practiced as if it didn't exist outside the universities. By ignoring the popular conception of what geography is, we foster a dangerous opposition between geography as a popular subject and geography as a discipline. I argue that the survival of the discipline requires a collective rediscovery of a common core, which could be built around ‘regional’ geography—not the outmoded capes, bays and main export regional geography of the past, but one informed by modern theory, and attending to causal structures rooted in current realities. Our introductory courses are the best place to demonstrate a renewed commitment to a holistic geography grounded in an understanding of the world. Eclectic, curiosity‐driven research is also essential to the survival of the discipline, but disciplinary diversity is a strength only if it is grounded in an identifiable core. Excessive pluralism and intellectual arrogance may lead to ‘disciplinocide’.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.084 | 0.039 |
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".