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Record W2591975586 · doi:10.1177/2158244017697166

Indigenous Peoples’ Attitude Toward Their Elders and Associated Personality Correlates

2017· article· en· W2591975586 on OpenAlexaffabout
Nakita-Rose Morrisseau, Joseph M. Caswell, Amber H. Sinclair, Paul M. Valliant

Bibliographic record

VenueSAGE Open · 2017
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsLaurentian University
Fundersnot available
KeywordsIndigenousPersonalityPsychologyBig Five personality traitsPositive attitudeSocial psychologyGerontologyMedicineEcology

Abstract

fetched live from OpenAlex

Research has indicated there are cultural differences in attitudes toward seniors. Very few studies, however, have been undertaken to evaluate attitudes toward elders in indigenous populations in Canada. The current study was unique in this regard by asking indigenous participants ranging in age from 18 to 50 years to provide their attitudes toward their native elders. The research was conducted with people who live on reserve and off reserve in communities in Northern Ontario. We sought to understand the influence of gender and personality factors on attitudes toward elders. The Kogan’s Attitude Toward Old People Scale and Cattell’s 16 Personality Factor Questionnaires were used to investigate attitude and personality differences among an indigenous sample. Results indicated that indigenous people have positive attitudes toward elders. There were no significant gender or living arrangement differences for those living on or off reserve. Significant correlations were found between personality factors and attitudes toward the elders. Potential implications are discussed.

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)0.002
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 score0.138
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.095
GPT teacher head0.406
Teacher spread0.312 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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