Stepping-stones to the Edge: Artistic Expressions of Islandness in an Ocean of Islands
Bibliographic record
Abstract
Since the earliest of times, islands have captured the artistic imagination—and, often, for the artist who finds his or her muse in being ‘islanded’, the smaller the island the better. Archipelagos offer an ideal setting for artists who take their inspiration from place: on small islands off islands they can experience an intensity of island living they might not otherwise have on a main island: boundedness and connection, isolation and community. This paper examines expressions of islandness by artists who live on islands off islands that are poles apart—‘archipelagos’ of the Canadian North Atlantic and the Great Southern Ocean. It draws upon interviews with those artists and writers to consider the nature of humans’ attachment and attraction to islands, exploring through the lens of phenomenology what Stratford et al. call the “entanglement between and among islands”.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".