Testicular Awareness: The What, the Why, and the How
Bibliographic record
Abstract
Globally, men have a lower life expectancy than women and health outcomes among men are poorer than women. Only Australia, Brazil, Iran, and Ireland possess national men’s health policies. Testicular disorders can have a negative effect on men’s health and are rarely addressed in these policies. Findings from the empirical literature on men’s awareness of testicular disorders suggest that men’s knowledge of testicular disorders is lacking and their intentions to seek timely medical attention for testicular symptoms are low. This paper aims to introduce the concept of ’testicular awareness’ and explore its implications for health research, practice, and education. The key attributes of ‘testicular awareness’ include: (i) familiarity with own testes; (ii) knowing what is normal versus abnormal; (iii) ability to detect an abnormality; and (iv) knowing own risk factors. Testicular awareness is an all-encompassing concept since it helps men become familiar with an intimate body part that is seldom discussed and enables them to detect testicular abnormalities and to seek timely medical attention for testicular symptoms, regardless of the ultimate diagnosis. Testicular awareness can be promoted using a number of strategies, such as: (i) involving men in drafting men’s health policies that address testicular awareness; (ii) partnering with men to develop and test interventions promoting testicular awareness; (iii) being cognizant of the learning needs of men who are at risk of health disparities including those with low literacy and health literacy; (iv) promoting testicular awareness in clinical practice and health education; and (v) using men’s daily spheres of information to promote testicular awareness; these include but are not limited to: workplaces, universities, gyms, and community organizations.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".