MétaCan
Menu
Back to cohort
Record W2953855235 · doi:10.18723/diw_dwr:2019-14-1

The Low-Wage Sector in Germany Is Larger Than Previously Assumed

2019· article· en· W2953855235 on OpenAlexaboutno aff
Markus M. Grabka, Carsten Schröder

Bibliographic record

VenueEconstor (Econstor) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLow wageWageQuarter (Canadian coin)Labour economicsOrder (exchange)EconomicsWage growthMinimum wageWage shareDistribution (mathematics)Efficiency wageDemographic economicsFinanceGeography

Abstract

fetched live from OpenAlex

The total number of dependent employees in Germany has increased by more than four million since the financial crisis. Part of this growth took place in the low-wage sector. Analyses based on data from the Socio-Economic Panel, which in 2017 for the first time include detailed information on secondary employment, show that there were around nine million low-wage employment contracts in Germany that year, around one quarter of all contracts. Women, young adults and employees in Eastern Germany are particularly likely to receive low wages. The legal minimum wage introduced in 2015 is below the low-wage threshold, and thus did not decrease the proportion of low-wage employees, although wages at the bottom-end of the distribution did markedly increase. Wage mobility has hardly changed since the mid-1990s: almost two thirds of employees in the lowest wage category were still there three years later. In order to curtail the low-wage sector, a better and broader qualification of workers, as well as a more proactive wage policy are called for. A reform of the mini-job rules would also be helpful.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.999

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.015
GPT teacher head0.279
Teacher spread0.264 · 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.

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

Citations14
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEconstor (Econstor)Same topicSocial Policy and Reform StudiesFrench-language works237,207