Effects of Cultural Matching and Identity Safety: An Examination of Indigenous Student’s School Experiences
Bibliographic record
Abstract
Cultural matching refers to the reflection of one’s own culture in day-to-day life, which is critical for nurturing one’s sense of acceptance and identity in the world (Rip et.al., 2020). Identity safety is when one’s social identity is welcomed and valued rather than viewed as a barrier to success The presence of cultural matching and identity safety is important in educational settings throughout childhood and adolescence, as both are crucial to students’ overall well-being and identity. Opportunities to express one’s culture in the classroom is essential for a sense of belonging and safety (Steele & Cohen-Vargas, 2013); however, Indigenous students do not often experience such opportunities. Using Indigenous Research Methodologies (e.g., Kovach, 2009), an Indigenous researcher interviewed Indigenous participants (N = 7) attending the University of Montana. Qualitative data analyses were conducted via audio-recorded, in-person interviews, which were then transcribed through Zoom. Participants were asked to share their experiences of cultural matching and identity safety regarding their school environments. Research team members then analyzed data to delineate common themes, which included both negative experiences due to a lack of cultural matching, as well as positive experiences when cultural matching was present. The results of the current study will highlight the effects of those experiences on Indigenous students and provide implications and applications for students at the University of Montana. Implications for this research will help us to identify barriers that Indigenous students are currently facing within their educational settings and will help us understand what components can effectively promote a culturally rich and safe environment for future Indigenous students. References Cohn-Vargas, Esther & Steele, Dorothy. (2013). Identity Safe Classrooms: Places to Belong and Learn. Kovach, M. (2009). Indigenous methodologies: Characteristics, conversations and contexts. Toronto: University of Toronto Press. Rip, J., Zijlstra, E., Post, W., Kalverboer, M., & Knorth, E.J. (2020). Cultural matching factors, child factors and fostering factors associated with successful foster placement: An explorative study into the perspectives of unaccompanied refugee children, their foster carers and guardians. Children and Youth Services Review, 118, 105408. Windchief, S., & San Pedro, T. (2019). Applying indigenous research methods: Storying with peoples and communities New York, NY: Routledge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".