‘Small Places like St Helena have Big Questions to Ask’: The Inaugural Lecture of a Professor of Island Geography
Bibliographic record
Abstract
This publication takes the form of a written version of my inaugural lecture, which was presented at Queen’s University Belfast on 10 March 2010. It is more personal and considerably more self-indulgent than would normally be acceptable in an article, with more of my own experiences and also my own references than would usually be considered proper. However, the bestowal of such a title as Professor of Island Geography is something of a marker of the maturity not just of me but maybe also for island studies. After a section describing my path into island geography, the lecture deals with the negativities of islands and the seeming futility of studying them, only then to identify a new or at least enhanced regard for islands as places with which to interact and to examine. Reference is made to islands throughout the world, but with some focus on the small islands off Ireland. The development of island studies as a discipline is then briefly described before the lecture concludes with reference to its title quotation on St Helena by considering that place’s islandness and how this affected/affects it in both the 17th and 21st centuries.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".