Geographical Gerontology: Mapping a Disciplinary Intersection
Bibliographic record
Abstract
Abstract The intersection between geography and gerontology arises structurally in institutions and intellectually both in academic debates surrounding disciplinary territoriality and substantive fields of empirical inquiry (population ageing and movement; services and policy; living environments; emplacement; emotions, images and the body). Although recent years have witnessed an increasing theoretical convergence between geography and gerontology – resulting in ever fertile ground for research – a range of contemporary social processes have yet to receive substantive attention. Arising as consumer niches and economic networks, these involve connectivity across geographical scales from the local to the global. Although they provide opportunities and enrich lives, they also contribute to the continued disadvantage of older people in the developing world. We argue that addressing these in research is not only morally justifiable, it potentially generates a distinct body of theoretical knowledge that might inform ongoing empirical work.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.017 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".