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Record W2778708134 · doi:10.22381/jrgs7120174

RECESSION AND RECOVERY IN SCOTLAND: THE IMPACT ON WOMEN’S LABOR MARKET PARTICIPATION BEYOND THE HEADLINE STATISTICS

2017· article· en· W2778708134 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of Research in Gender Studies · 2017
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRecessionHeadlineEconomicsLabour economicsEarningsDemographic economicsUnpaid workQuarter (Canadian coin)WelfareUnemploymentWork (physics)Economic growthGeographyBusiness

Abstract

fetched live from OpenAlex

This article examines the impact of the great recession and subsequent economic recovery on the position of women within the labor market in Scotland. In common with other developed economies, Scotland experienced the most serious financial crisis since 1929 and the longest and deepest recession since the early 1930s. Despite this, the economic data would suggest that women’s position in the labor market has improved significantly over recent years as the economy began to recover as there are now a record number of women in employment. However, using secondary literature and official labor market figures, this article argues that the data only tells part of the story since a lot of these jobs could be described as precarious, involving atypical contracts of employment. That is the job does not involve a full– time contract of employment with a single employer for an indefinite period. The article concludes that the increase in women’s participation in the formal labor market has not resulted in a significant improvement in gender equality nor has it led to a redistribution of unpaid work between women and men.

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.331
GPT teacher head0.610
Teacher spread0.279 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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