Letter to the Editor on “Does blue balls exist, and why should we care?”
Bibliographic record
Abstract
Jones et al recently published an expert opinion piece questioning whether the phenomenon of blue balls is real and why the answer to this question matters.1 The authors performed a thorough literature review on blue balls and epididymal hypertension, and they included a descriptive analysis of posts on a Reddit forum for women-identified individuals who experienced pressure or coercion due to blue balls. They concluded that evidence for the phenomenon of blue balls is nearly nonexistent and suggested that it might be better understood as a form of somatization rather than a purely physiologic condition. The authors also concluded that scientific circles have largely dismissed this phenomenon because of its perceived harmlessness and that instances of coercion and sexual violence, as exemplified by the examples provided in their piece, highlight the risks of dismissing the potentially devastating effects of blue balls. As a result, the authors called for more research to provide clarity on the phenomenon and possibly prevent sexual violence.
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.021 | 0.021 |
| Insufficient payload (model declined to judge) | 0.020 | 0.014 |
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".