The Skin of Nostalgia: A Reflection on the Artifice of Postcards, Structuralist Filmmaking, and Home Movies.
Bibliographic record
Abstract
Widespread culture are infamously sentimental, sometimes trite, and often mundane. Feelings of nostalgia are often as benign as they are malevolent: a balm for the troubled soul, a poisonous dependence on the old ways, a reprieve from the drab pallor of day-to-day life, and most commonly a harmless escape to a time when things seemed better. I will argue that nostalgia is more than the passive preservation and restoration of the past; nostalgia, is a (positive) re-possession of the past through the continuous rehearsal of the familiar – the past is essentially structured by the present, with how and what is remembered, and how and what is forgotten. The picture postcard and the amateur film are examples of a certain kind of 20th century aesthetic toward "exoticism" and "authenticism," the retrieval of the peripheral, and the redemption of the ephemeral. Nostalgia is characteristically ambivalent. It is the classical and often more personal version of a wistful remembrance of by-gone days has given way to a post-modern version of rapidly consumable nostalgias. This essay, however is concerned with the more the personal version of nostalgia, and is a reflection on my artistic practice as method for interrogating the senses of longing and loss, which infuse the present.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.035 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".