“I Was Worshiped and in Control”: Sugar Arrangements Involving Transactional Sex from the Perspective of Both Sugar Babies and Sugar Benefactors
Bibliographic record
Abstract
Sugar dating arrangements involve an older partner (“sugar daddy/mommy”) who provides financial support to a younger partner (“sugar baby”) in exchange for intimacy. The current study recruited a U.S. and Canadian sample of sugar babies (n = 45) and sugar benefactors (n = 32) through social media sources to survey them about perceived power in their sugar arrangement, gender roles, and stigma. Sugar benefactors did not differ in perceived power from sugar babies, nor in endorsement of traditional gender roles or stigma. Directed content analysis analyzing open-ended responses about associated outcomes indicated that both partners placed strong emphasis on companionship despite the importance of sex within arrangements. Sugar babies reported that money drives participation, although arrangements fulfill other needs, such as pleasure. Other benefits include having an arrangement with clear boundaries and expectations. Disadvantages include concerns for safety, that being physical safety for babies, and reputation and being used for money for daddies. Notably, both groups perceived sugar babies as having equal or more power than sugar benefactors, although this was often attributed to sugar babies’ attractiveness and youth. Findings include insights from both babies and benefactors, and support perspectives that sugar dating is distinct from traditional sex work.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".