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Record W3137482683 · doi:10.55016/ojs/sppp.v12i1.58358

Public Sector Wages in Alberta: How do these Compare to Other Provinces and to the Private Sector?

2019· article· en· W3137482683 on OpenAlexafffundabout
Richard Mueller

Bibliographic record

VenueThe School of Public Policy Publications · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsUniversity of Lethbridge
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchUniversity of LethbridgeUniversity of Calgary
KeywordsPublic sectorPrivate sectorBusinessLabour economicsEconomicsEconomic growthEconomy

Abstract

fetched live from OpenAlex

We use a variety of methodologies to address how the public-private sector wage premium in Alberta compares to those of other provinces, how these differ by type and level of public sector employment (e.g., federal, local, etc.), by the location in the overall wage distribution, and if the wage premium in this sector varies over the business cycle. We find a great deal of heterogeneity in the public sector wages premium by province and type of public sector employment. While estimates do differ, generally the premium in Alberta is among the lowest in Canada, tends to be higher for local and provincial employees, is higher at the lower tail of the wage distribution, and is inversely related to the Alberta business cycle. The estimates suggest significant savings to the Alberta government are possible, but that across-the-board cuts to Alberta employee compensation could have negative implications for the provision of public services.

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)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.303
Teacher spread0.252 · 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
Published2019
Admission routes3
Has abstractyes

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