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Record W4402639968 · doi:10.7202/1113397ar

Exploring Maternalism: Brigitte Bardot, Baby Seals, and Contemporary Hegemonies of the Female Hero

2023· article· en· W4402639968 on OpenAlexaffvenueabout
Arielle Frenette, Caroline Desbiens, Julia Christensen, Justine Gagnon

Bibliographic record

VenueÉtudes/Inuit/Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsQueen's UniversityUniversité Laval
Fundersnot available
KeywordsHEROGender studiesArtSociologyLiterature

Abstract

fetched live from OpenAlex

Imperial tales of heroic exploration have had long-lasting effects on the construction of colonial landscapes and of hegemonies of masculinity centered on whiteness, physical strength, and endurance. This paper examines the renewal of such heroic polar explorer narratives in recent times, and how recurring stories tend to re-create as well as produce new hegemonies around gender and race. Through a case study of the expedition of Brigitte Bardot on the Canadian ice shield in 1977 with the intent of saving baby seals, this paper looks at neocolonial implications of a contemporary polar expedition narrative as told by a female “hero”. We argue that BB’s story is “maternalist” in that it is symbolically benevolent but reaffirms colonial authority on Inuit lands and practices based on a discourse of moral virtue and emotional care. Interestingly, the framing of seal pups as “babies” has constructed the act of sealing as gendered and motherhood as an important standpoint for both anti-sealing activism and Inuit pro-sealing resistance.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0120.018
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.452
GPT teacher head0.331
Teacher spread0.121 · 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 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

Citations0
Published2023
Admission routes3
Has abstractyes

Explore more

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