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Record W1441629589 · doi:10.26686/lew.v0i0.1671

Work Arrangements in New Zealand: First Results from the Survey of Working Life

2008· article· en· W1441629589 on OpenAlexaboutno aff
Michelle Barnes, Sharon Boyd, Sophie Flynn

Bibliographic record

VenueLabour Employment and Work in New Zealand · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCasualDiversity (politics)Quarter (Canadian coin)Work (physics)Demographic economicsJob satisfactionSurvey data collectionLabour economicsBusinessPsychologySociologyEngineeringGeographyPolitical scienceEconomicsSocial psychologyMathematics

Abstract

fetched live from OpenAlex

Work arrangements in New Zealand have changed substantially in the last 30 years, leading to increased diversity in contracting arrangements, hours and times worked, and terms and conditions of employment. This paper describes the current work arrangements, employment conditions and job satisfaction levels of employed people in New Zealander from data collected in the Survey of Working Life. The survey was run as a supplement to the Household Labour Force Survey in the March 2008 quarter, to answer questions such as: 'How prevalent is casual work in New Zealand?', 'How many employed people work non-standard hours?’ and 'Who is most likely to experience stress or discrimination at work?’ The focus o f the data analysis is to identify workers with different types of employment relationships (for example, temporary versus permanent employees), and describe the demographic and job characteristics associated with these different employment relationships. Working-time patterns and conditions of employment are the other key topics examined in this paper. It is intended that this supplement be repeated every three years to monitor changes in employment conditions, work arrangements and job quality in New Zealand.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.154
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.093
GPT teacher head0.316
Teacher spread0.223 · 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 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
Published2008
Admission routes1
Has abstractyes

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