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Record W3016321589 · doi:10.22215/etd/2020-13913

Securitizing the Canadian Family Through Transnational Reproductive Governmentality and Citizenship

2020· dissertation· en· W3016321589 on OpenAlexafffundabout
Mary G. Jessome

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsCarleton University
FundersGovernment of Canada
KeywordsGovernmentalityCitizenshipBiopowerFraming (construction)PoliticsPolitical scienceCorporate governanceNegotiationGovernment (linguistics)State (computer science)Gender studiesSociologyPublic administrationPolitical economyLawGeography

Abstract

fetched live from OpenAlex

Putting top-down and bottom-up understandings of Canadian reproductive bio-politics into dialogue by acknowledging the link that reproductive citizenship forges between familial and national reproduction, I focus on procreative practice of transnational surrogacy as a form of nation building.Methodologically, this involves using intersectional governmentality as a lens for critical policy analysis and a critical discourse analysis of Joseph Tito's social media accounts.Tito is a Canadian parent who used a Kenya-based surrogacy arrangement and had his twin daughters rendered stateless at the end of the process.This approach allows me to make three main arguments.First, I determine that the Government of Canada relies on a decentralized and globalizing regime of government to manage such families, incorporating actors, institutions, technologies, and policies located at various geospatial sites.Second, to secure the nation-state from possible threats, this system of governance can lead to citizenship deprivation for children born through transnational surrogacy.Thirdly, despite the Government of Canada framing the families as a threat and the possible complications that their offspring face, Canadian families whose children were produced transnationally can act as securitized governmental actors.They do so through a negotiation of state regulation and employing bio-political discourses that echo the racialized, gendered, classed, and ableist ideologies initiated during Canada's eugenic beginnings as a settler-colony.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.112
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0290.031
Scholarly communication0.0090.003
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.047
GPT teacher head0.315
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2020
Admission routes3
Has abstractyes

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Same topicReproductive Health and TechnologiesFrench-language works237,207