Bibliographic record
Abstract
The affective labour debate has become mainstream in communications studies. In this paper, I The affective labour debate has become mainstream in communications studies. In this paper, I suggest the Aesthetic Movement of the late 19th century as inspiration for how users can use Facebook with the knowledge that their data is being used for profit. I present Facebook usage as art, creating an analog with aesthete Oscar Wilde’s essay, “the critic as artist” (1891/2010), where he presents critics as artists. Other theorists, especially Walter Benjamin provide grounding for making the argument that Facebook usage is an artistic expression. I then turn to my inversion of Walter Pater’s “art for art’s sake”, the seminal idea of Aestheticism and propose Facebook for Facebook’s sake as a method for Facebook use. While more advanced remuneration concepts have yet to arrive with such force that they could provide the proper payment to users, Facebook for its own sake is a way to appreciate Facebook’s beauty in the meantime. Baudelaire and Debord’s psychogeographic theories provide methods for navigating cities that I apply to examine Facebook as a digital city. The central claim of this paper is the following: By using Facebook for Facebook’s sake, users take back some of the dignity taken away from them in the exploitation of free labour. Finally, I turn to critiques of Aestheticism and how contemporary software might provide insight into using Facebook in an ethical manner. Users will have to consider each action differently; how would liking something affect users’ artistic expression of themselves? In this way, while the affective labour debate continues, users can use Facebook for its own sake.
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 | 0.003 | 0.010 |
| 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 | 0.015 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".