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Record W2017118670 · doi:10.1159/000345775

On Being Indigenous: An Essay on the Hermeneutics of ‘Cultural Identity'

2013· article· en· W2017118670 on OpenAlexaff
Michael J. Chandler

Bibliographic record

VenueHuman Development · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIndigenousIdentity (music)SociologyGender studiesIdentity formationImmigrationTransition (genetics)RefugeeAestheticsSocial sciencePolitical scienceSelf-conceptLaw

Abstract

fetched live from OpenAlex

The range of cultural resources distributed along developmental pathways open to young persons as they frame the outlines of their own identities is not fixed, but inevitably varies across historical moments. The young lives most touched by such transitional circumstances arguably belong to those that find themselves growing up in times of dramatic cultural change - the lives, for example, of refugee and immigrant children, and especially of those indigenous youth still riding out the successive waves of earlier postcolonial storms. This essay is about forming an identity in such troubled times, and about how individual parents and whole rearing communities might choose to selectively intervene. The thesis of this paper is that the material contents of cultures in transition ordinarily have shorter ‘shelf lives' and earlier ‘best before' dates than do those processes and practices at work in the procedural background. Consequently, it is argued that a parent's or a community's best hopes for success in aiding young people in their identity struggles lie along instructional pathways that feature the signature tools and processes, rather than the material contents, of cultures in radical transition.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.021
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0090.044
Scholarly communication0.0080.009
Open science0.0010.003
Research integrity0.0030.007
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 head0.034
GPT teacher head0.326
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 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

Citations28
Published2013
Admission routes1
Has abstractyes

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