MétaCan
Menu
Back to cohort
Record W1480779235 · doi:10.22329/celt.v7i1.3997

Cultural Safety for Mi’kmaw Students and Staff at Cape Breton University

2014· article· en· W1480779235 on OpenAlexaffvenueabout
Heather Schmidt

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsCape Breton University
Fundersnot available
KeywordsIndigenousMainstreamEthnic groupContext (archaeology)SociologyPedagogyPsychological interventionNova scotiaCultural safetyCultural diversityHigher educationPublic relationsPsychologyPolitical scienceEthnologyAnthropologyGeography

Abstract

fetched live from OpenAlex

Cultural safety reflects the extent to which an individual feels that their culture is respected, accepted and understood by the larger society in which they live.The concept was originally developed in the context of Indigenous Peoples, but it could also easily be applied to members of other minority groups whose voices are underrepresented in mainstream society (e.g., the LGBT community, the differently-abled, other ethnic minorities). In this paper, I discuss my ongoing efforts to assess and measure cultural safety in Mi’kmaw First Nation students, staff and faculty at a small university in northern Nova Scotia. To maximize the chances of Indigenous students graduating and achieving to their full-potential within post-secondary institutions, we need to stop and ask whether they feel a sense of belonging, connection and cultural safety on-campus. If the answer is ‘No’ or ‘Only in the Aboriginal student centre’, then we need to collaborate with Indigenous students to design and implement interventions. These may involve altering both the physical campus and the way in which non-Native individuals on-campus think about and relate to Indigenous culture and individuals.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.912
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0220.004
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.020
GPT teacher head0.301
Teacher spread0.282 · 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
Published2014
Admission routes3
Has abstractyes

Explore more

Same venueCollected Essays on Learning and TeachingSame topicService-Learning and Community EngagementFrench-language works237,207