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Record W2275351047 · doi:10.7202/1035385ar

Situating Canada’s Commercial Surrogacy Ban in a Transnational Context: A Postcolonial Feminist Call for Legalization and Public Funding

2016· article· en· W2275351047 on OpenAlexvenueaboutno aff
Maneesha Deckha

Bibliographic record

VenueMcGill Law Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsLegalizationCommodificationPolitical scienceContext (archaeology)Gender studiesSociologyPublic spherePoliticsLawEconomy

Abstract

fetched live from OpenAlex

In large part due to feminist interventions in the early 1990s about the dangers of assisted reproductive technologies (ARTs) for women, Canada banned several practices related to ARTs when it enacted the Assisted Human Reproduction Act ( AHRA ) in 2004. Notably, the AHRA prohibited commercial surrogacy. Feminists feared that a market in surrogacy would exploit and objectify marginalized Canadian women who would be pressured into renting out their wombs to bear children for privileged couples. Since the early feminist deliberations that led to the ban, surrogacy has globalized. Canadians and other citizens of the Global North routinely travel to the Global South to source gestational surrogates. In doing so, they partake in an industry that heavily depends on material disparities and discursive ideologies of gender, class, and race. Indeed, the transnational nature of surrogacy treatment substantially reshapes the earlier feminist commodification debates informing the AHRA that took the domestic sphere as the presumed terrain of contestation. Due to the transnational North-South nature of surrogacy, a postcolonial feminist perspective should guide feminist input on whether to allow commercial surrogacy in Canada. I argue that when this framework is applied to the issue, the resulting analysis favours legalization of commercial surrogacy in Canada as well as public funding for domestic surrogacy services and ancillary ARTs.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
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 head0.048
GPT teacher head0.306
Teacher spread0.258 · 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
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

Citations9
Published2016
Admission routes2
Has abstractyes

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