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Record W4382466647 · doi:10.2478/ijme-2023-0012

Influence of the COVID-19 pandemic on the transition of people on the Polish labor market – hidden threats

2023· article· en· W4382466647 on OpenAlexaboutno aff
Grażyna Węgrzyn

Bibliographic record

VenueInternational Journal of Management and Economics · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicQuarter (Canadian coin)UnemploymentCoronavirus disease 2019 (COVID-19)Labour economicsEconomicsSplit labor market theoryDemographic economicsSecondary labor marketBusinessEconomic growthLabor relationsGeographyMedicine

Abstract

fetched live from OpenAlex

Abstract The article analyzes changes on the Polish labor market after the outbreak of the COVID-19 pandemic. It aims to assess the effect of the SARS-CoV-2 pandemic on the transition of people on the labor market in Poland. The decided majority of research into the effects of the COVID-19 pandemic on the labor market was based exclusively on resource analysis, omitting stream analysis. This research fills this gap and provides analysis by quarter of the transition of people on the labor market between employment, unemployment, and professional inactivity. The COVID-19 pandemic caused a severe drop in the number of people in work in the second quarter of 2020, similar in level to an analogous increase in the number of people professionally inactive. The effects of the pandemic were much more severe for women than for men. Detailed analysis of transitions on the labor market shows that around 50% of jobs lost due to the outbreak of the pandemic were not regained. Many redundancies were permanent, which may translate into a weakening of the dynamic for the recovery of the labor market in the future.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.274
Teacher spread0.221 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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