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Record W4237861758 · doi:10.4324/9781003062219-13

Women in Management in Canada

2020· book-chapter· en· W4237861758 on OpenAlexaboutno aff
Golchehreh Sohrab, Rekha Karambayya, Ronald J. Burke

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

This chapter discusses the status of women in management in Canada to take stock of changes in women&s;s participation in the workplace and recent initiatives on the part of employers to improve the roles and retention of women in managerial ranks. Compared to men, women are disproportionately represented in the part-time workforce, including part-time, contract and non-standard work arrangements. Canadian legislation to support women in the workplace is enshrined at the constitutional, federal and provincial levels. Federal employment and labour laws, such as the Canada Labour Code and the Canadian Human Rights Act cover less than 10 percent of the Canadian workforce. The chapter provides an overview of organizational initiatives intended to support women’s career advancement based on three pillars: empowering women, developing unbiased procedures, and building inclusive environments. In conclusion, improving the lot of women in management may require concerted effort on three fronts: government, employers and the general population.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.180
Threshold uncertainty score0.951

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.008
Science and technology studies0.0280.005
Scholarly communication0.0100.002
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0210.001

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 head0.107
GPT teacher head0.242
Teacher spread0.135 · 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 designObservational
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

Citations2
Published2020
Admission routes1
Has abstractno

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