MétaCan
Menu
Back to cohort
Record W6988042039

Women in Northern Ireland 2020

2020· other· en· W6988042039 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Education Resource Archive (University College London) · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentQuarter (Canadian coin)Northern irelandUnemployment rateWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

The following publication considers the different labour market experiences of women and men in Northern Ireland.A consistent feature of the labour market is higher employment and unemployment rates for males and higher inactivity rates for females.These features are explored using estimates from the Labour Force Survey quarterly and household datasets. Key Points: The employment rate for males in NI has been consistently higher than for females over the past ten years.Although the number of employees in NI was evenly split between males and females in 2019, the number of self-employed males was more than double the number of self-employed females. Males were more likely to work full-time than females.Furthermore, approximately 60% of employed women with dependent children worked full-time, compared to 95% of employed males with dependent children. The unemployment rate for males in NI has been consistently higher than for females over the past ten years, however, the gap is narrowing between the two.In 2019, 44% of the unemployed were female and 56% were male. Over the past 10 years there have been consistently more economically inactive women than men.In 2019, just under a third of working age women were economically inactive, compared to just under a quarter of 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.008

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 head0.005
GPT teacher head0.185
Teacher spread0.180 · 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; both teacher heads agree on what is shown here.

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueDigital Education Resource Archive (University College London)French-language works237,207