Bibliographic record
Abstract
Abstract | The text-essay by Karen Engle, “Fragments of Desire,” and photo-essay by Trudi Lynn Smith, “Finding Aid: NxW,” together form a conversation intended to explore connections between photography, truth, impossibility, and failure within photography in present-day Waterton Lakes National Park, Canada. In response to the provocation of this special issue, Smith selected pieces from her archival artwork Finding Aid and mailed it to Engle, who wrote the essay in response to her encounter with the archive. When Smith received the essay, she created a photo-essay from the archive in response to Engle’s text.Résumé | L’essai de Karen Engle « Fragments de désir » et le reportage photo de Trudi Lynn Smith forment une conversation ayant pour but d’explorer la connexion entre photographie, vérité, impossible et échec dans la photographie contemporaine du parc national Waterton Lakes. En réponse au défi posé par cette édition spéciale, Smith a sélectionné des images de son œuvre archivistique Finding aid puis les a envoyées à Engle qui a écrit son essai à partir de son interaction avec ces documents d’archives. Suite à la réception de l’essai, Smith a créé le reportage photo à partir des archives en réponse au texte d’Engle.
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 | 0.003 |
| 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 | 0.023 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 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".