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Record W2145575716 · doi:10.25336/p6zw3s

Unemployment of people of foreign origin in France: The role of discrimination

2013· article· en· W2145575716 on OpenAlexvenueno aff
Jean‐Luc Richard

Bibliographic record

VenueCanadian Studies in Population · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsNationalityUnemploymentCitizenshipImmigrationDemographic economicsCensusSample (material)Position (finance)PopulationPoliticsForeign bornSociologyDemographyPolitical scienceEconomicsEconomic growthLaw

Abstract

fetched live from OpenAlex

This article has two primary objectives: (1) to understand the relationship between the origins of the children of immigrants and the likelihood of unemployment; and (2) to examine the possible role of discrimination in the likelihood of unemployment. The French Permanent Demographic Sample (EDP, a longitudinal database maintained by INSEE, which is the French equivalent of the English Longitudinal Survey) permits the study young foreign-born people who grew up in France and young people of foreign-origin who were born in France. The EDP is a census-based panel survey that, on average, comprises a 1 per cent sample of all immigrant groups. It contains information on a person’s nationality relative to his/her labour market position. According to most academics, it also contains valuable socio-demographic and socio-economic information on parents and their sons and daughters. The data registry was created in 1967 and includes data from the 1968, 1975, 1982, 1990, and 1999 censuses. The interest in individual trajectories requires us to consider the relations between personal labour market situations and the acquisition of French nationality. This relation must be analyzed in light of the population which consists of those children who, since childhood, have been in a position to acquire French citizenship. Although gaining citizenship is usually regarded as an important sign of civic and political assimilation among immigrants, it can also be seen as a factor in their economic assimilation. French nationality makes it easier for young immigrants to get jobs. It is better to be a young Algerian or Moroccan with French nationality than to be a young Algerian or Moroccan who does not have French nationality.

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)0.000
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 score0.132
Threshold uncertainty score0.152

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 head0.037
GPT teacher head0.318
Teacher spread0.280 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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