Notes on an Eternal Return: Photographic Self-Portraiture and the Spectral Subject
Bibliographic record
Abstract
Focusing on the characteristics of ghostliness and haunting, my MA thesis project considers spectrality as a lens to rethink representations of otherness in photographic self-portraiture. Spectrality, a metaphor within the humanities, and now applied to visual art, foregrounds the presence of what is absent and testifies to the invisible aspects of our socially constructed subjectivities. I question how photographic self-portraiture initiates a dissociative transformation for the subject, and apply this line of questioning to an analysis of works by Claude Cahun, Suzy Lake, Eleanor Antin, and Mona Hatoum. I analyze how these artists present intentionally othered versions of themselves, by exploring and re-performing the intricacies of their identities. I support this research with a body of artistic work, where I embody the self-as-other and present myself as a spectral subject as a means to understand how we can rethink representations of the female body and female subjectivity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".