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Record W3192062823 · doi:10.3386/w29119

Native Americans’ Experience of Chronic Distress in the USA

2021· preprint· en· W3192062823 on OpenAlexaff
David G. Blanchflower, Donna Feir

Bibliographic record

VenueNational Bureau of Economic Research · 2021
Typepreprint
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsDistressPsychologyEnvironmental scienceClinical psychology

Abstract

fetched live from OpenAlex

Four million Native Americans who identify as single race live in the USA. Another three million identify as Native American in combination with another race. Yet they are rarely the focus of detailed research. We provide the first evidence that levels of consistently poor mental health, or chronic distress, among Native peoples were greater in every year between 1993 and 2020 than among White or Black Americans. We find this to be present among those over the age of thirty but less so for the young. Over time we demonstrate there has been a rise in chronic distress among Native Americans and multi-race individuals. However, chronic distress seems to be lowest among Native peoples living in the seven states with the largest Native American populations of Alaska, Arizona, Montana, New Mexico, North Dakota, South Dakota and Oklahoma. In our judgment these facts are important and not widely known. This stands in stark contrast to the enormous scholarly and media interest in declining physiological well-being among White Americans.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.417
GPT teacher head0.582
Teacher spread0.165 · 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 designTheoretical or conceptual
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

Citations19
Published2021
Admission routes1
Has abstractyes

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