Bibliographic record
Abstract
The idea that context shapes text is traceable to Aristotle who identified poetry or "making" with the form or plot that best appeals to audience expectations. Today's complex world, with its host of competing truths, requires texts that reflect this confusion. My novel reacts to this context, appealing to expectations in both form and story. What are those expectations? The current appetite for shorter texts and the popularity of the short novel might be explained by a growing alliterate population, an educated group who value books, but who have little time to read them. Yet reading hasn't declined altogether. Current event periodicals like Harper's and The Atlantic have seen a dramatic increase in circulation since 9/11. These magazines are the home of the short essay, with alliterate expectations clearly in mind. With Photoblur I've responded with fictional fragments that acknowledge the reduced attention span of today's readers. But I don't confuse alliterate with illiterate. The novel's disordered form mirrors world events, particularly 9/11, fragmenting further in the pages following the destruction. The philosophical digressions are representative of the inter-mingling of short essay and fiction, linking the story with questions underlying the story. It is text shaped by context. Loaded with contradiction, it satirizes the postmodern world (and its players, preoccupations, performances, etc.) using postmodern devices. It pines for the past, but refuses to conform to its conventions. It weaves thematic threads, but some get tied in knots, and others disappear clear off the page. The title, Photoblur, speaks to my fascination with blurs; those incomplete, unfinished stories. The unresolved moment. An image in flux, as Michael Ondaatje observed, "shapeless, awkward, moving to the clear." Source: Masters Abstracts International, Volume: 42-01, page: 0059. Adviser: Di Brandt. Thesis (M.A.)--University of Windsor (Canada), 2003.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.322 | 0.123 |
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".