Nosthetics: Instagram poetry and the convergence of digital media and literature
Bibliographic record
Abstract
This article considers the proliferation of nostalgic aesthetics in Instagram poetry (‘instapoetry’). Though often overlooked, the relationship between the platform and the poetry itself is a vibrant entry point into debates about the handwritten, analogue and vintage styles of instapoetry. Connecting modernist and postmodernist arguments about nostalgia, this article provides a critical and conceptual lens with which to analyse the visual aspects of nostalgic aesthetics – referred to as ‘nosthetics’ – characteristic of instapoetry, investigating how and why the genre impersonates the pre-digital, analogue past. Combining scholarship on platforms, nostalgia and instapoetry shows how the concept of nosthetics can be used as a framework for literary and visual analysis of instapoetry. The theoretical framework proposed recommends three developments for those researching nostalgic aesthetics in instapoetry. First, greater attention should be paid to the platform. Second, engagement with scholarship on popular culture and nostalgia is needed. Finally, it is insightful to return to the notion of space at the heart of Johannes Hofer's original definition of nostalgia.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".