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Record W4410431802 · doi:10.1007/978-3-031-91371-6_6

Gender and Sex Entanglement in Neuroscience

2025· book-chapter· en· W4410431802 on OpenAlexaff
Annie Duchesne

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldNeuroscience
TopicNeuroscience, Education and Cognitive Function
Canadian institutionsUniversité du Québec à Trois-RivièresUniversity of Northern British Columbia
Fundersnot available
KeywordsQuantum entanglementPsychologyNeuroscienceCognitive sciencePhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

From the discovery of the gonadal neuroendocrine axis to projects mapping gender/sex diferences in brain and behavior, research in neuroscience has laid the foundation in biosciences for the investigation of sex and, to a lesser degree, gender. Given its role in sex and gender research, neuroscience has also been a central site of critical engagement by feminist science scholars, giving rise to neurofeminism, a subfeld where neuroscience and feminist perspectives on science intersect. To date, neurofeminism has produced critiques, research frameworks, methodologies, epistemologies, and neuroscientifc knowledge that coalesce to advance complex and emancipatory understandings of brain, body, and mind. This chapter aims to demonstrate the instrumental role of neurofeminist research and perspectives in producing alternative operationalizations of sex and gender, particularly with respect to their interrelation. First, a critical overview of dominant and emerging models for investigating sex and gender in neuroscience is provided to highlight benefts of approaching sex and gender as biosocially entangled. Second, the neurofeminist perspective on sex and gender entanglement is further characterized through a series of examples from human and nonhuman animal research. Consideration is then given to potential challenges associated with the neurofeminist approach to entanglement. Finally, the generative potential of neurofeminist science scholarship to improve the science of sex and gender is demonstrated.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.952
Threshold uncertainty score0.962

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.294
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2025
Admission routes1
Has abstractyes

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