MétaCan
Menu
Back to cohort
Record W2135442563 · doi:10.6000/1929-4409.2012.01.3

“That Time of Month:” Premenstrual Dysphoric Disorder in the Criminal Law-Another Look

2012· article· en· W2135442563 on OpenAlexaffvenue
Rosanna Langer

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2012
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsLaurentian University
Fundersnot available
KeywordsPremenstrual dysphoric disorderCulpabilityDiminished responsibilityPsychologyPsychiatryMoodMental healthBiopsychosocial modelCriminal lawCriminologyMedicineMenstrual cycle

Abstract

fetched live from OpenAlex

This paper argues that women suffering from pre-menstrual dysphoric disorder (PMDD) ought to have available to them a range of legal defences that accurately reflect culpability. As PMDD focuses primarily on emotional mood and behavioural symptoms as opposed to physical manifestations of the premenstrual period, legal treatment of PMDD can be usefully compared to other “disordered states” that affect mental capacity, rationality and intent. Evolution of PMDD as a distinctive form of psychiatric disorder warrants a new consideration of the dual feminist concerns about the invisibility of women in criminal law theory and the undue labeling of all women. This article considers the application of criminal law defenses in light of newer research characterizing pre-menstrual mental disorder as a dynamic psychiatric and physiological state with shifting determinants that may be experienced differently over time. Ultimately, criminology must grapple with developing an account of women’s criminality that reflects accurately women’s lives lived within the sometimes overwhelming experience of biopsychosocial stressors. Reviewing PMDD in light of these concerns supports an enhanced understanding of the dynamics between women’s mental health and culpability.

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 score0.305
Threshold uncertainty score0.281

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 studies0.0000.001
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 head0.065
GPT teacher head0.354
Teacher spread0.288 · 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

Citations1
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Criminology and SociologySame topicMenstrual Health and DisordersFrench-language works237,207