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Record W2792469080 · doi:10.1080/14649365.2018.1433867

Reconfiguring the breastfeeding body in urban public spaces

2018· article· en· W2792469080 on OpenAlexafffundabout
Vanessa Mathews

Bibliographic record

VenueSocial & Cultural Geography · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsUniversity of Regina
FundersUniversity of Regina
KeywordsBreastfeedingGender studiesSociologyNormativePublic spaceHuman sexualityEmbodied cognitionNegotiationIdentity (music)AestheticsPolitical scienceArtSocial scienceLawMedicine

Abstract

fetched live from OpenAlex

The breastfeeding body is subject to overt and subversive forms of regulation and control in contemporary society, where it is sexualized and naturalized, rendered both visible and invisible, revered and found disruptive. Despite health policy espousing the benefits of breastfeeding for mother and child, duration rates in Canada remain relatively low. In this paper, I explore the spatial practices of the breastfeeding body in public, using feminist work on the body and theorizations of built form, urban space and embodied practice. Drawing on a series of feminist autoethnographic vignettes, I write my breastfeeding body into a diversity of routine urban spaces – a car, grocery store, mall, bookstore, highway, alleyway – and narrate my experiences negotiating social responses and spatial arrangements. I argue that the breastfeeding body challenges normative understandings of gender, motherhood and sexuality through its participation and presence in public space. The breastfeeding body transgresses the meaning of space and the performance of identity as it claims space for private use.

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)0.002
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.018
Scholarly communication0.0060.003
Open science0.0010.007
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.039
GPT teacher head0.312
Teacher spread0.273 · 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

Citations35
Published2018
Admission routes3
Has abstractyes

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