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Are Men Animals?: How Modern Masculinity Sells Men Short, by Matthew Gutmann

2023· article· en· W4387122652 on OpenAlexaffvenue
Mary‐Lee Mulholland

Bibliographic record

VenueAnthropologica · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsMount Royal University
Fundersnot available
KeywordsMasculinitySociologyGender studies

Abstract

fetched live from OpenAlex

T he nature-nurture debate is perhaps one of the most enduring debates within anthropology and one of anthropology's greatest contributions to public understanding of human behaviour.Most famously, Boas and his students championed cultural relativism while successfully critiquing scientific racists and eugenicists who worked to naturalize racialized categories.These same anthropologists, most notably Margaret Mead, also critiqued the biological determinism of gender, sex and sexuality.In Are Men Animals?How Modern Masculinity Sells Men Short, anthropologist Matthew Gutmann challenges us to ask why "racialized ideas about biological capacities" have been largely rejected (except of course within white supremacy) "but beliefs about men's biological capacities and animal urges" have not (2019: 229).Drawing on research in the natural and social sciences, including his own multi-sited ethnographic research on masculinity in China, Mexico and the United States, Gutmann argues that the entrenchment of gendered behaviour, specifically toxic masculinity, as biological, is the result of social processes including cultural perceptions of gender and sexuality, confirmation bias and folk science.In the spirit of anthropology's contribution to public understanding of gender and sex, this book is written for a public audience rather than an academic one, and this has some advantages and costs.The book is very accessible and excerpts would make a great addition to undergraduate courses on the anthropology of gender.However, more specialized researchers may be left longing for more concrete examples of recent research that challenges the myth of testosterone and other biological agents of gender.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.352
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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