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Record W1990054275 · doi:10.1108/01437720910973034

Workplace responses to vacancies and skill shortages in Canada

2009· article· en· W1990054275 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Manpower · 2009
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsOvertimeEconomic shortageOriginalityWork (physics)BusinessProbit modelLabour economicsOrder (exchange)Ordered probitWageEconomicsDemographic economicsActuarial sciencePsychologyFinanceEngineeringSocial psychologyEconometrics

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to analyze employer responses to vacancies and skill shortages by adopting certain workplace practices. Design/methodology/approach Making use of the longitudinal nature of the Workplace and Employee Survey, a nationally representative sample of Canadian organizations, the paper applies both linear and probit models to examine incidence of positive vacancies and vacancy rates and subsequent adoptions of various workplace practices in response to such vacancies and skill shortages. Findings Employers respond to labour and skill shortages in a number of ways, focusing more on short‐term and less costly solutions, such as adoption of flexible working hours and increases in overtime hours, greater reliance on flexible job design and part‐time workers, and implementation of self‐directed work groups and problem‐solving teams. There is no evidence that workplaces would raise employee wages or fringe benefits to alleviate shortages. Practical implications In the absence of a well‐developed internal market, firms are likely to continue using short‐term and less costly solutions. Governments should work with firms, workers and their representatives and act strategically to resolve issues of timely identification of skill shortages in order to make informed decisions and put mechanisms in place to address such shortages. Originality/value The results are based on a national longitudinal survey and a number of important practical and policy implications are discussed in the paper

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.950

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 studies0.0000.000
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 head0.025
GPT teacher head0.397
Teacher spread0.373 · 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