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Record W1511437467 · doi:10.1177/117718011401000405

Indigenous Peoples’ Life Stories: Voices of ancient knowledge

2014· article· en· W1511437467 on OpenAlexafffund
Stan Bird

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2014
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsFirst Nations Health and Social Secretariat of Manitoba
FundersUniversity of Calgary
KeywordsIndigenousNarrativeMeaning (existential)Traditional knowledgeConstruct (python library)Gender studiesSociologyPsychologyHistoryAnthropologyLiteratureArtEcology

Abstract

fetched live from OpenAlex

Narrative is a meaning-making tool used broadly across cultures. Individuals use their particular cultural narrative to interpret experiences and construct a personal narrative or life story. This research focused on the life stories of Anishinaabe people, an Indigenous group of the North American Great Lakes region, whose history is characterized by attempts at assimilation into the dominant Western culture. We sought to understand if maintaining traditional Indigenous knowledge affected meaning-making in life stories. Participants included four groups of volunteers: Elders and young adults, with and without traditional Indigenous knowledge. Results showed that the narratives of the two traditional Indigenous knowledge groups evidenced statistically significant greater efficacy and personal resolve than those of the non-traditional groups. Additionally, the Elder traditionalists’ narratives showed significantly greater involvement with existential/spiritual issues than other groups. We concluded that traditional Indigenous knowledge positively shaped participants’ narratives, thus confirming the importance of cultural narratives in the meaning-making process.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.353
Teacher spread0.325 · 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.

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
Published2014
Admission routes2
Has abstractyes

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