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Record W230442347

An Explanation of Human Rape: An Integration of Sociobiology and Social Science

2014· article· en· W230442347 on OpenAlexaff
Krystle George

Bibliographic record

VenueScholarship@Western (Western University) · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsWestern University
Fundersnot available
KeywordsSociobiologySociologyCriminologyEpistemologyAnthropologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

The study of human rape within a sociobiological framework has been a topic of public debate for decades, most notably after the release of biologist Edward O. Wilson’s book Sociobiology: The New Synthesis (1975). As sociobiology is based on the theory of evolution, Wilson’s book analyzed the social behaviour of animals, thus asserting that their social adaptations can be compared to the social behaviours of human-beings (Clark, 1991). Through this sociobiological framework various social behaviours of humans were addressed for further study, including the controversial subject of human rape (Clark, 1991). Among the supporters of this framework, none are as infamous as biologist Randy Thornhill and anthropologist Craig Palmer, who co-wrote A Natural History of Rape: Biological Bases of Sexual Coercion (2000). This notorious book outlines several possible human rape adaptations, virtually all of which concern reproductive strategies. The works of such authors have been criticized by the social sciences, including feminist academics like Susan Brownmiller, who claim that rape is not about sex, but power and domination (Thompson, 2009). Meanwhile, many sociobiology supporters, including Thornhill and Palmer (2000), maintain that rape is about sexual desire, and claim that the social sciences lack merit in their research on rape because their theories do not consider the evolutionary causes of human behaviour (p. xi). As this essay will demonstrate, both cultural and evolutionary forces have been shown to have considerable effects on the occurrence of rape. Therefore, I argue for an integration of both approaches in order to successfully understand and thus potentially prevent and eradicate rape.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.131
GPT teacher head0.380
Teacher spread0.249 · 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 designObservational
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
Published2014
Admission routes1
Has abstractyes

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