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Record W7001231392

An Investigation of Virginity in Adulthood

2024· dissertation· en· W7001231392 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2024
Typedissertation
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsnot available
Fundersnot available
KeywordsVirginity testAmbiguityPopulationFace (sociological concept)Value (mathematics)Young adult
DOInot available

Abstract

fetched live from OpenAlex

Canadian population data estimate that 21 to 42% of young adults aged 18 to 24 could be considered virgins, having never engaged in vaginal or anal sex. Virginity, however, is a difficult concept to define, in part due to ambiguity about what constitutes sex. This complexity is heightened for LGBTQ+ individuals, who often view virginity as a primarily heterosexual concept. Broadly, this dissertation aimed to investigate the concept of virginity in adulthood. Through a series of three separate online studies and using both quantitative and qualitative methods, this research program focused on adults’ definitions of sex, abstinence, and virginity; the characteristics and experiences of self-identified virgins and how they compare to non-virgins; and the dating and relationship experiences of virgin adults and their partners. Overall, participants’ broadest definition was for virginity. LGBTQ+ participants had broader definitions of sex and narrower definitions of virginity than their heterosexual counterparts. Adult virgins face pervasive stigma, leading to negative emotions and dating discrimination. The results support characterizing adult virginity as a concealable stigmatized identity. Despite this stigma, virgins show considerable resilience, with many finding value in their virginity and those in relationships reporting a high degree of relationship satisfaction. The studies collectively show that adult virgins are not a homogenous group; their experiences, attitudes, and behaviours vary widely. Implications for educational, healthcare, and legal settings and future research directions are discussed.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.227
Teacher spread0.218 · 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 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
Published2024
Admission routes1
Has abstractyes

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