Bibliographic record
Abstract
SUMMARY The following photo/text work is an extract from a much larger installation of photographs and text. The photographs have a modified generic quality: colour landscapes and self-portraits in tourist sites across America, the images similar to postcards or amateur tourist/family photographs. The stories, by contrast, are grounded in an individual specificity of response to the sites and events of the trip to function as allegorical anecdotes. The work conjoins a personal, lesbian and poetic narrative with familiar and potentially mundane images. The format of the tourist plaque is an appropriation of the trope of ‘official’ authority that uses such markers to direct and define what is currently and historically significant. The work explores questions of: the ambiguity of identity through association, lesbian invisibility, cross gender play, homo/lesbo eroticism, women'S access to and ownership of public space, the imaginary of the ‘road trip,’ landscape in photography, the documentary function of photography, photographic history, heterosexual assumption, etc. The work constructs a lesbian cognitive map of space, place, memory and history. The work (initially) appears simple in presenting familiar imagery with personal stories that explore theoretical ideas of lesbian subjecthood.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.204 | 0.122 |
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".