Geography, pedagogy and politics
Bibliographic record
Abstract
This Forum takes seriously the proposition that everything we do as geographers is potentially `relevant' to the affairs of the wider society. Using expanded conceptions of `pedagogy' and `politics', the Forum suggests why and how we are always engaged in processes of shaping and steering this wider society, wittingly or not, and intentionally or not. In the minds of many of us, this shaping and steering only (or mostly) occurs through activities we assume to be self-evidently `relevant' in intention or effect — like undertaking policy-relevant research. However, this Forum argues that it is misplaced to regard only a select group of our activities as socially consequential. Pulling together recent debates on `participatory', `activist' and `public' geographies, the Forum offers arguments and examples that show readers the potential relevance of the whole range of diverse practices in which we professionally engage. The introduction and five subsequent contributions together suggest that we aim for a `joined-up' conception of ourselves and our activities as professional geographers embedded in a wider society. As such, the Forum aims to make a distinctive contribution to ongoing discussions of how big-G academic geography relates to the plethora of small-g quotidian geographies — imagined and real — that are the stuff of our world.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 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".