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Record W2036624386 · doi:10.1177/1523422306288432

An Ojibwe American Indian View of Adult Learning in the Workplace

2006· article· en· W2036624386 on OpenAlexaboutno aff
Linda LeGarde Grover, Karen M. Keenan

Bibliographic record

VenueAdvances in Developing Human Resources · 2006
Typearticle
Languageen
FieldPsychology
TopicHuman Resource Development and Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Cultural diversitySociologyCultural knowledgePublic relationsEnvironmental ethicsPolitical scienceAnthropologyPedagogy

Abstract

fetched live from OpenAlex

The problem and the solution. Human resource development professionals have, in recent years, given increasing attention to fostering diversity and epistemological, or “world view” inclusiveness in the workplace. However, although research exists on many diverse groups, little exists on the management and development of American Indian workers. Various cultural aspects of the ways in which American Indians view existence affecting learning, of knowledge sharing, developing skills, and applying skill and knowledge to task, are unfamiliar to many Westerners. Many HRD professionals would likely benefit from knowledge of and familiarity with American Indian culture and worldview, knowledge that would surely enhance their ability to (a) communicate effectively with and within those communities and (b) include some aspects of American Indian epistemology that might complement or intersect with their own lives and work. This article focuses on the Ojibwe Indians of the North Central United States and southern Canada.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.182
Threshold uncertainty score0.362

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.012
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.344
Teacher spread0.328 · 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 designQualitative
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

Citations9
Published2006
Admission routes1
Has abstractyes

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