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Record W7133057817

An Exploration of Implicit Attitudes toward Indigenous Peoples in Canada and Managing Settler Biases through Mindfulness

2020· dissertation· W7133057817 on OpenAlexaffabout
Kristina Klopfer

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsIndigenousImplicit-association testFeelingMindfulnessPopulationRacismIntervention (counseling)Test (biology)Association (psychology)
DOInot available

Abstract

fetched live from OpenAlex

The consequences of colonization and racism continue to impact the lives of Indigenous Peoples in Canada, notably within the healthcare system. The two studies forming this dissertation turned the research lens onto Settler peoples in Canada. The overarching goals were to develop a tool that could be used to identify levels of implicit bias toward Indigenous Peoples, examine the relationships between mindfulness, self-compassion, emotions, and measures of racial/ethnic bias, and investigate differences in reactions, feelings of warmth toward Indigenous Peoples, and intentions for change associated with administering a brief mindfulness intervention after receiving implicit bias feedback. Study 1 developed the Indigenous Peoples in Canada Implicit Association Test (IPC-IAT), an adaptation of the well-known Implicit Association Test (IAT; Greenwald, McGee, Schwartz, 1998). Data was collected from 306 White self-identified individuals from the general Canadian population. Analyses identified moderate levels of implicit negative bias toward Indigenous Peoples in Canada and found that the IPC-IAT showed expected relationships to other measures and established correlates of racial/ethnic bias. Few significant correlations between measures of racial/ethnic bias, mindfulness, self-compassion, and emotions were revealed. Study 2 explored the acceptability of the IPC-IAT and whether a brief self-compassion intervention administered after the IPC-IAT lessened negative reactions, improved feelings of warmth toward Indigenous Peoples, and led to greater intentions for change. Both healthcare professionals (n = 13) and those from the general population found the IPC-IAT to be an acceptable component of an assessment of, and brief intervention for, racial/ethnic biases. A group of 95 individuals randomly assigned to receive the brief self-compassion intervention was compared to a control group (n = 89) that completed unrelated reading and writing tasks following IPC-IAT feedback. Intervention did not promote the expected changes in state-mindfulness and those assigned to the intervention group did not have fewer negative reactions, greater feelings of warmth, or more intentions for change compared to the control group. Post-exploratory analyses showed that positive reactions were correlated with greater feelings of warmth and intentions for change. Implications and limitations of both studies are discussed and future directions for addressing Indigenous-specific racism are considered.

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)0.003
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: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.048
GPT teacher head0.367
Teacher spread0.320 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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