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Record W4233985619 · doi:10.24124/2017/54744

A collection of aboriginal stories and wisdoms for counsellor development

2017· dissertation· en· W4233985619 on OpenAlexfundno aff
Judy Letendre

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsnot available
FundersUniversity of Northern British Columbia
KeywordsIndigenousMainstreamMulticulturalismDiversity (politics)CurriculumRacismIndigenous educationTraditional knowledgePedagogySociologyCultural safetyGender studiesPublic relationsPolitical scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Current mainstream counselling education is Euro-American based; a practice presenting other worldviews, including Indigenous, as sidelines categorized under umbrella terms such as multiculturalism, diversity or cultural competency. This relatively singular lens misses the depth in counselling practices and often sees other cultures incorrectly and leads to misunderstandings or unhelpful, even harmful practices like racism. Aboriginal stories and wisdoms have been gathered to develop Indigenous curriculum that will share equal educational space. For this project, I combined Indigenous principles and protocols and standard qualitative methods to gather and analyze the information. I interviewed Aboriginal people I had known previously from various BC Nations as unique individuals holding wisdom and knowledge passed to them through their Indigenous ancestry, and with various connections to counselling as a client, counsellor, educator and/or course developer. Their collective voice suggests Indigenous knowledge be delivered in an Indigenous way using heart learning and spiritual purpose, teachings seen as absent in in western based counselor education.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

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

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 head0.031
GPT teacher head0.396
Teacher spread0.364 · 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 designNot applicable
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

Citations1
Published2017
Admission routes1
Has abstractyes

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