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Record W2955442906 · doi:10.5604/01.3001.0014.0678

Work calculator: a useful tool for modelling relations on the labour market

2018· article· en· W2955442906 on OpenAlexaboutno aff
Maria Bieć, Ewa Gałecka‐Burdziak, Robert Pater

Bibliographic record

VenueWiadomości Statystyczne The Polish Statistician · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLabour Market and Migration
Canadian institutionsnot available
Fundersnot available
KeywordsCalculatorUnemploymentQuarter (Canadian coin)Work (physics)Computer scienceDivision of labourEconometricsEconomicsLabour economicsOperations researchMacroeconomicsEngineering

Abstract

fetched live from OpenAlex

The aim of the article is to present the concept of a job calculator — a tool used to create a simulation of relations between changes in the economic situation and the labour market in Poland. The job calculator is based on the American Jobs Calculator and is available for everyone. The user determines the height of expected unemployment rate and the tool computes the number of required job offers, the creation and coverage of which will result in the change of the unemployment rate to the predefined level. The calculator uses data from the Labour Force Survey (LFS) and presents simulations for one quarter. The values refer to the total result, taking into account the seasonal fluctuations and division into long-term and cyclical changes, which is the authors’ contribution to the original American model as well as an extension of this concept.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.007

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 head0.033
GPT teacher head0.302
Teacher spread0.268 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2018
Admission routes1
Has abstractyes

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