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Record W4404760477 · doi:10.1215/00703370-11679677

The Intergenerational Legacy of Indian Residential Schools

2024· article· en· W4404760477 on OpenAlexaboutno aff
Maggie Jones

Bibliographic record

VenueDemography · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousSocioeconomic statusHuman capitalEducational attainmentGovernment (linguistics)Residential schoolEconomic growthSociologyCultural capitalSocioeconomicsGeographyPolitical sciencePopulationDemographySocial scienceEconomics

Abstract

fetched live from OpenAlex

From the late nineteenth century until the end of the twentieth century, the Canadian government collaborated with Christian churches to operate a network of boarding schools for Indigenous children to culturally and economically assimilate them. These children were taken from their families and placed into residential schools, where they were to be assimilated into the Eurocentric culture of the dominant society. Using a unique restricted-access database that asked Indigenous respondents about their family history with residential schools, in addition to questions on socioeconomic outcomes, I study the intergenerational effects of these schools. Despite previous research showing that residential schools increased human capital accumulation among attendees, I find that residential schools are associated with lower educational attainment among subsequent generations. I present evidence consistent with the notion that both cultural detachment and a breakdown in family relationships contributed to a reversal of the standard relationship between parents' and children's human capital. Encouragingly, I find suggestive evidence that greater access to cultural centers might buffer the harmful legacy of this historical trauma.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.120
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0010.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.302
Teacher spread0.292 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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