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Record W4282965212 · doi:10.3167/fpcs.2022.400103

A “Capital of Hope and Disappointments”

2022· article· en· W4282965212 on OpenAlexaff
Dustin Alan Harris

Bibliographic record

VenueFrench Politics Culture & Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsSocial Sciences and Humanities Research CouncilYork University
Fundersnot available
KeywordsWelfareImmigrationSocial WelfarePopulationGovernment (linguistics)Economic growthSocial capitalPolitical scienceSociologyEconomicsLawDemography

Abstract

fetched live from OpenAlex

This article traces the history of specialized social housing for North African families living in shantytowns in Marseille from the early 1950s to the mid-1970s. During the Algerian War, social housing assistance formed part of a welfare network that exclusively sought to “integrate” Algerian migrants into French society. Through shantytown clearance and rehousing initiatives, government officials and social service providers encouraged shantytown-dwelling Algerian families to adopt the customs of France’s majority White population. Following the Algerian War, France moved away from delivering Algerian-focused welfare and instead developed an expanded immigrant welfare network. Despite this shift, some officials and social service providers remained fixated on the presence and ethno-racial differences of Algerians and other North Africans in Marseille’s shantytowns. Into the mid-1970s, this fixation shaped local social assistance and produced discord between the promise and implementation of specialized social housing that hindered shantytown-dwelling North African families’ incorporation into French society.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.999

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 studies0.0010.001
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 head0.059
GPT teacher head0.361
Teacher spread0.303 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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