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Record W2794749022 · doi:10.1017/9781108235556.030

Organizational Culture in the Context of National Culture

2018· book-chapter· en· W2794749022 on OpenAlexaff
T. Alexandra Beauregard, Kelly Basile, Cynthia A. Thompson

Bibliographic record

VenueCambridge University Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOrganizational cultureContext (archaeology)SociologyBusinessPolitical scienceGeographyPublic relationsArchaeology

Abstract

fetched live from OpenAlex

An organization's culture can have a profound impact on how its employees with caregiving responsibilities experience their work and family roles (Shockley, in press;Thompson, Beauvais & Lyness, 1999).At the same time, national culture also influences individuals' preferences for how they manage those roles.For instance, workaholism among men is more common in cultures centered on achievement and material success than in cultures that emphasize quality of life; women are less likely to work outside the home in cultures featuring a strong breadwinner/homemaker gender role ideology (Lewis, 2009;Snir & Harpaz, 2009).Given that globalization has increased international mobility for workers as well as the likelihood that home country workers are interacting with colleagues from or in other countries (Tams & Arthur, 2007), it has become paramount for work-family scholarship to recognize that multiple layers of culture are increasingly influencing employees' experiences in integrating work and family, as well as their perceptions of appropriate organizational work-family practices.It is important for work-family scholars to determine the efficacy of organizational work-family practices and policies, as these practices continue to expand beyond their Western points of origin and become implemented all over the world (e.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.807
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.239
Teacher spread0.211 · 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 teacher head, 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

Citations16
Published2018
Admission routes1
Has abstractyes

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