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Record W4249438846 · doi:10.24124/2005/bpgub362

Brown Sheep, Brown Landscape: Australia as I Remember It.

2005· dissertation· en· W4249438846 on OpenAlexaff
Danielle Sarandon

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicAustralian History and Society
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsGender studiesPeriod (music)Perspective (graphical)Baby boomMiddle classImmigrationPersonal identityIdentity (music)Life course approachBoomPersonal lifeWorld War IISociologyFamily lifePsychologySocial psychologyPolitical scienceSocial scienceAestheticsLawDemographyEngineeringArtSelf-concept

Abstract

fetched live from OpenAlex

In the following pages, I present my personal perspective on the 1950s and 1960s in Australia's development, with particular emphasis on the Second World War, the Baby Boom, the Vietnam War, women's experiences with family life and gender formation, and immigration. In this life writing, I illustrate my personal knowledge of the stresses on middle class family life during the 1950s. I also examine the conflicting desires of many middle class women to experience fulfillment in the workplace, while at the same time conforming to the societal expectations of women in suburban family life. As well, I explore personal gender and sexual identity formation pressures that I experienced as I tried to meet patriarchal expectations for young women during this period. My personal experiences have greatly informed my analysis of the social expectations for women during this period.

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)0.000
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0070.002
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0250.006

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 head0.046
GPT teacher head0.357
Teacher spread0.311 · 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
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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