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Record W3125487818

The Frontier, Entrepreneurialism, and Engineers: Women Coping with a Web of Masculinities in an Organizational Culture

2002· article· en· W3125487818 on OpenAlexaffabout
Gloria E. Miller

Bibliographic record

VenueSSRN Electronic Journal · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsFrontierSociologyValue (mathematics)EthnographyWomen entrepreneursGender studiesInterviewOrganizational cultureValue systemsSocial psychologyPsychologyPublic relationsPolitical scienceEntrepreneurshipSocial science
DOInot available

Abstract

fetched live from OpenAlex

The experiences of Canadian women in the oil industry are studied to gain insight into the role of gender in this largely masculine industry.The oil industry has a masculine value system, as demonstrated through five dominant themes of the industry:the frontier myth (idea of a cowboy hero with particular approach to life and work), an entrepreneurial belief system, an entrepreneurial value system that reinforces work divisions by gender, interactions that rely on masculine interests and paternalistic behaviors toward women, and adaptation strategies by women that reinforce the masculine value system. Data were collected by interviewing 20 women (varying in years of experience and positions) working in the oil industry.Prevalence of the five themes is investigated using an interpretive ethnographic analysis.Results confirm the dominance of masculine themes that create a dense cultural web of assumptions, beliefs, and values within the industry, making them difficult to change.There is a need for feminine characteristics to be incorporated into masculine organizational cultures if women are to seen as equally valuable. (AKP)

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.014
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.019
GPT teacher head0.223
Teacher spread0.204 · 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
Published2002
Admission routes2
Has abstractyes

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