Bibliographic record
Abstract
Abstract Benevolent sexism is a subtle yet pervasive form of sexism that portrays women as wonderful yet weak. While more overt and hostile sexist attitudes have become less acceptable, especially in Western countries, benevolent sexism often goes unchallenged and is not always recognized as sexist. However, growing evidence indicates that benevolent sexism is dangerous, as it subtly and insidiously undermines gender equity. Benevolent sexism negatively affects women in the workplace, both when decision-makers (interpersonal effects) and when women themselves (intrapersonal effects) endorse these attitudes. Decision-makers who hold benevolent sexist views may undermine women’s professional outcomes through seemingly positive yet patronizing actions that are perceived as harmless. For example, they may refrain from giving women challenging assignments to protect them, even though such tasks are essential for career advancement. Additionally, benevolent sexism may not directly harm women’s outcomes but can advantage men, such as when funders’ benevolent sexism does not affect evaluations of women’s pitches but positively influences evaluations of men’s pitches. Women who endorse or are exposed to benevolent sexism also experience diminished performance, lower career aspirations, and a reduced likelihood of challenging the status quo. Future research about benevolent sexism and gender equity in the workplace should (a) expand the scope of outcomes to include workplace sexual harassment, (b) adopt an intersectional approach, and (c) examine benevolent sexism in societies that are not Western, educated, industrialized, rich, and democratic (WEIRD). Although limited research exists, studies have shown benevolent sexism’s mixed effects on workplace sexual harassment—ranging from a decreased likelihood of recognizing harassment to negative association between benevolent sexism and violent behavior, which may indicate that benevolent sexism has protective properties but only when it is directed at women adhering to traditional gender roles. Further, as most studies have focused on women in general, often implicitly assuming they are White, there are gaps in the understanding of how benevolent sexism affects non-White women, sexual-minority women, women with disabilities, those who speak different languages or with different accents, and individuals with nonbinary gender identities. Last, limited research from non-WEIRD countries, e.g., Turkey, Argentina, South Africa, and Pakistan, provides preliminary insights into the undermining effects of benevolent sexism beyond the typical Western context. Addressing this subtle yet pervasive form of sexism requires a global perspective to effectively promote gender equity in the workplace and society at large. To achieve this, research must extend beyond the United States and other Western countries and must involve a more diverse group of scholars who can bring in varied voices and perspectives.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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".