Bibliographic record
Abstract
Islands have inspired a history of folklore, literary genres and artistic visual work, continually captivating human creativity and imagination.This multi-media article presents work that moves beyond traditional boundaries of the educational field to link nationally with the Institute of Island Studies, located at the University of Prince Edward Island, Canada, and internationally with the Small Island Cultures Research Initiative, hosted by the Island Cultures Centre at Macquarie University in Sydney, Australia.Through the vehicle of video, interweaving imagery and improvisational music, the artist-researcher examines island as a distinctive geographical site and the spatial dimensions of island locality.The author applies methods of visual poetic inquiry while integrating perspectives of image-based arts with disciplines of island studies, philosophy, and human/cultural geography.The intentionality of the work is to stimulate a multi-layered "trans-disciplinary" approach (Baldacchino, 2006) to island studies and qualitative research and to represent the emergent process of developing an island aesthetic methodology.The aim of the article is to expand island studies
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.035 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".