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Record W4213022522 · doi:10.5772/intechopen.101721

Spoken and Unspoken between Indigenous and Non-Indigenous: Trust at the Heart of Intercultural Professional Collaborations

2022· book-chapter· en· W4213022522 on OpenAlexaff
Émilie Deschênes, Sébastien Arcand

Bibliographic record

VenueIntechOpen eBooks · 2022
Typebook-chapter
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsHEC MontréalUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsIndigenousContext (archaeology)Social relationSociologyPolitical sciencePublic relationsSocial scienceGeographyEcology

Abstract

fetched live from OpenAlex

Several contemporary societies are facing important issues regarding the relations between Indigenous and non-Indigenous populations. The difficulties of establishing dialogs based on lasting positive intercultural relations have repercussions within the institutions and organizations of a given society. Between the affective and relational sphere and the professional sphere, links are forged, which reproduce complex social relationships, even conflicting ones. This is the context in which our chapter’s proposal fits. By focusing on the determinants of social relations at work in these daily encounters between non-Indigenous and Indigenous in the workplace and the bonds of trust, or mistrust, which ensue, we will question the premises of social relations between non-Indigenous and Indigenous. These questions emanate from various research studies that we have carried out in recent years in organizations in the mining and energy sectors.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.012
Scholarly communication0.0080.007
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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