Bibliographic record
Abstract
Panography is a series of linked poems that develops a disjunctive narrative from a simple premise: it transplants the figure of Pan into the backwoods of contemporary northern Ontario, on the fringes of a rural community. This idea owes much to Knut Hamsun's novel Pan , which places a Pan-like protagonist on the outskirts of a Norwegian village. Unlike Hamsun's Pan, Panography overtly acknowledges Pan's multiplicity as a cultural figure by juxtaposing its own Pan-narrative with nods to (and appropriations of) his appearances in classical mythology and literary iconography, and his rare invocations in contemporary popular culture. Panography is an examination of rural Canadian ideas of masculinity, an exploration of the backwoods story as social cement, a love poem to the details of the northern Ontario landscape, and a vaguely Jungian study of what happens when psychology embraces the natural world as its substrate (claiming that, despite cosmopolitan postmodernity, this is still possible). Panography is neither transcendentalist nor environmentalist in its primary agenda. Pan, as a hybrid of the human and the bestial, and as an archetype that has been carried to the present exclusively through artistic and scholarly works, is an ideal nexus for a deconstruction (or even a synthesis) of the received binary of art and nature. Panography allows its readers to escape the filtered aesthetic of much literary nature writing, in which the process of artistic representation places nature itself in a subordinate position, fit merely for terror, sentimentality or pathetic fallacy.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.368 | 0.114 |
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".