Masculinity, femininity, and leadership: Taking a closer look at the alpha female
Bibliographic record
Abstract
An extensive review and textual analysis of the academic and popular literature of the human alpha female was conducted to examine the social construction and expression of the alpha female identity in a small non-random sample of North American women (N = 398). This review revealed 2 predominant alpha female representations in the literature-one more masculine versus one more feminine-and 21 alpha female variables. In this sample of women, the "alpha female" was found to be a recognized socially constructed female identity. Univariate analysis revealed positive and highly significant differences in self-reported mean scores between alpha (N = 94) and non-alpha (N = 304) females for 10 variables including, masculine traits, leadership, strength, low introversion, self-esteem, life satisfaction, sexual experience, initiates sex, enjoys sex and playing a dominant role in sexual encounters, with alpha females scoring higher than non-alphas. The measure of masculine traits was identified as the only predictor of alpha female status as per the multiple regression model. Interestingly, both alpha and non-alpha women scored the same for the measure of feminine traits. Further, both groups scored higher for feminine traits than masculine traits. The results also revealed that neither social dominance nor sexual dominance were predictors of alpha female status which challenge academic and popularized representations of this identity. The results suggest that although the alpha female is often regarded as an exceptional and, at times, an exoticized form of femininity, like other femininities, her identity is marked by contradictions and tensions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".