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Record W3158139015 · doi:10.24908/iqurcp.7626

Desperate Housewives and Soccer Moms: Examining the relationship between media representations and the lived reality of women in the suburbs

2017· article· en· W3158139015 on OpenAlexvenueno aff
Jessica White

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsDepictionFemininityIdeal (ethics)Gender studiesSociologyPoliticsAestheticsPolitical scienceArtVisual artsLaw

Abstract

fetched live from OpenAlex

Has suburbia ever truly met the needs of the populations it claims to serve? Since its creation suburbia has been a centre of conflict between the image created by the media and lived realities. The post war images of femininity in the suburbs were ones of domesticity and a heteronormative family. In essence the “sitcom” family was created and reality was made to look like its television counterpart. Yet in real life, did any family look like that of Leave it to Beaver? Have our ideals of the perfect family living in the perfect house truly changed? If they have changed have they had an effect on policy makers and land developers? A brief historical examination of suburbia, its creation, and media images will be contrasted with the developments and policies we find in today’s suburbia. To partially answer my original question the demographic of women in suburbia, more specifically mothers will be discussed. Are today’s media images of suburbia a better depiction of lived realities or are urban political processes still at play to perpetuate an ideal image?

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)0.007
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 score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.007
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.409
GPT teacher head0.456
Teacher spread0.047 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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