Bibliographic record
Abstract
Abstract The concept of the alpha female has become widely accepted as a form of female identity in the West. Though relationships between hormone concentrations and alpha-related traits have been demonstrated in alpha nonhuman primates, this has not been examined in the case of the human alpha female. The present study examined the associations of testosterone and cortisol, as well as 3 other hormones, estradiol, oxytocin, and progesterone derived from hair samples, with 11 variables related to the expression of the alpha female identity in a small non-random sample (N=126) of self-identified alpha and non-alpha women in North America. The results revealed statistically significant differences between these groups. When compared to non-alpha women, alpha women scored higher than non-alphas in measures for masculinity, leadership, low introversion, self-esteem, and exhibited lower hair cortisol levels. Alphas exhibited slightly lower estradiol and oxytocin levels than non-alphas though these differences were non-significant. Similar non-significant differences were also found in the case of sexual experience, sexual dominance, testosterone, and progesterone. Though cortisol was not associated with masculine traits, it was positively and significantly associated with leadership. Cortisol was also negatively and significantly associated with strength and a measure for femininity. Progesterone, testosterone, and oxytocin were positively and significantly associated with enjoying sex, as was oxytocin with playing a dominant role in sexual encounters. Surprisingly, testosterone was not associated with alpha status nor with the measure of masculinity, and estradiol was not associated with any of the variables. The results imply that women who identify as alpha may experience less physiological stress than non-alpha females as measured by their lower cortisol levels.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".