Bibliographic record
Abstract
Titled “FOGO,” after the island of Fogo, Newfoundland, this collection speaks from the intersection of location, visitation, and residency. Fogo has drawn considerable attention for the artist residency program begun in 2010 by a native islander in an effort to revitalize the local communities. The titular island manifests the mystique of place as persona, person as place, and each poem is framed, ostensibly, in the voice of a male artist working in a different medium in residence on Fogo. While this project plays in persona, “FOGO” also interrogates narrative—each persona begins to tell a story or stories. Narrative arcs begin, or are entered at some point along a spectrum, but remain fragmentary. Slippage between the personas causes the narrative fragments to overlap, conflate and diverge. The text as a whole asks the reader to contemplate whether the fragments come together to create a coherent whole, and suggests that the reader will bring their own storytelling into the act of reading to ‘fill in the gaps.’ “FOGO” further represents ongoing exploration of interdisciplinarity. The heavy research undertaken to capture the special vocabularies of more than forty “types” of artist made it natural to adopt the abecedarian form. The volume comprises a disordered alphabet, a small encyclopedia of art and intimacy spoken by strangers in a strange land.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.078 | 0.019 |
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".