Avoiding the transactional “feel” while getting paid: Affect and relational work in sugar dating
Bibliographic record
Abstract
Following Viviana Zelizer's extensive scholarship on the interweaving of money and intimacy, this paper discusses the often overlooked yet critical role of affect in the production of relational work and in the success of relational packages. Drawing from the results of a grounded-theory-driven research study on sugar dating, the motions through which affect seeps through and structures negotiations of payments and emotional attachment are explored. The paper discusses the management of feelings as a component of relational work-so that arrangements neither feel too transactional nor too intimate-as well as the role that affect plays in differentiating sugar dating from illicit sexual transactions. It also contributes to the literature on sugar dating and sex work by critically discussing the limits of the commodification of intimate services and affect under a dominant belief system that rejects the possibility of selling "real" intimacy.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".