Editorial: Sex and gender effects on power, status, dominance, and leadership – an interdisciplinary look at human and other mammalian societies
Bibliographic record
Abstract
In human societies, men tend to have more power, status, dominance, and occupy leadership positions more often than women; similarly, in animal societies, power and dominance are often unequally distributed between males and females. Despite these similarities across societies of humans and animals, the scientific study of power, status, dominance, and leadership have (for the most part) progressed in isolation, with little cross-disciplinary exchange or fertilization between the natural and social sciences. In the social sciences, an extensive body of work has investigated the relation between gender (or sometimes sex) and power, status, dominance, and leadership outcomes (e.g., Eagly & Karau, 2002; Goldin, 2014; Eagly and Heilman, 2016; Meeussen et al., 2016; Hentschel et al., 2018; Von Rueden et al., 2018; Smith et al., 2020; Eckel et al., 2021; Shen et al., in press; Heilman et al., 2024). This effort notwithstanding, many questions remain. For example, we lack a comprehensive understanding of the contexts and circumstances that favor (or undermine) women’s advancement to powerful positions, and about why and when female and male leaders are evaluated differently (Williams and Tiedens, 2016; Cardador et al., 2022). In the natural sciences, empirical investigations in mammalian societies have primarily focused on the evolutionary origins and dynamics of male-female power asymmetries. Specifically, such investigations often focus on a few taxa with female dominance, such as bonobos, lemurs, and spotted hyenas (Kappeler, 1993; Lewis, 2018; Davidian et al., 2022; Smith et al. in this Research Topic). Notably, intersexual dominance–the distribution of power and status between the sexes—is often treated as a binary (i.e., a species is described as either male-dominant or female-dominant) and as a fixed (rather than flexible) trait of a given species (Lewis, 2018; Davidian, 2022). Contrary to this view, recent studies suggest the relative power of the sexes in some animal societies may be less biased in favor of one sex and more flexible than previously assumed (Kappeler et al.). With this Research Topic, we aim to facilitate academic exchange, to learn from perspectives that typically lie outside of each of our disciplinary boundaries, to draw comparisons and insights across these perspectives, and to promote an integrative understanding of gender and sex1 inequalities in power, status, dominance, and leadership. To do so, this Research Topic combines contributions from ecology, biology, psychology, and management. It houses a collection of 21 articles, including 10 articles from the social sciences and 11 articles from the natural sciences. We hope this trans-disciplinary Research Topic will not only deepen our understanding of the roots and origins of gender and sex inequalities in humans and non-humans, but also generate new insights into possible solutions for reducing sex and gender disparities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".