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Record W208395787

The Double-Edged Sword: Using the Criminal Law Against Female Genital Mutilation in Canada

2006· article· en· W208395787 on OpenAlexaffabout
Audrey Macklin

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRedressCitizenshipPoliticsPolitical scienceHuman rightsSociologyState (computer science)Power (physics)Gender studiesIdentity (music)NegotiationPosition (finance)ImmigrationLawCriminology
DOInot available

Abstract

fetched live from OpenAlex

The salient issue for most human rights activists working from within the communities where female genital mutilation (FGM) has been prevalent is not whether, but how, to eradicate the practice. This essay focuses on policies adopted in one country of immigration – Canada – in order to explore the complex positioning of women within diasporic communities. The author’s interest lies in the approach that emphasizes the procedural aspect of citizenship and promotes the participation of members of various identity groups in the political, social, and judicial institutions that shape the national community. This article considers questions such as: What are the risks and the benefits of using the legal system of the host country to redress one particularly stark manifestation of gender inequality within the diasporic community? Who is in the best position to make this assessment? What does the evidence to date suggest? The theoretical conundrum is clear: negotiating intragroup power relations within marginalized communities through resort to an apparatus of the state may help redress inequalities, but may simultaneously push the group as a whole further to the margins.

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 score0.525
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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

Citations4
Published2006
Admission routes2
Has abstractyes

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