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Record W7038123700

Hospitality and indigeneity in the K-12 school system

2023· dissertation· en· W7038123700 on OpenAlexaff

Bibliographic record

VenueMspace (University of Manitoba) · 2023
Typedissertation
Languageen
FieldMaterials Science
TopicDiatoms and Algae Research
Canadian institutionsGovernment of Manitoba
Fundersnot available
KeywordsHospitalityIndigenousSchool systemPopulationIndigenous educationSocial practice
DOInot available

Abstract

fetched live from OpenAlex

Educational hospitality, according to Claudia W. Ruitenberg (2011), is the notion that otherness is accepted, anticipated, and embraced. In a hospitable space, students are able to change practices that do not meet their unique needs, with pedagogy and practice becoming reflective of the population they serve, rather than perpetuating traditional understandings of schooling. Within a school context, hospitality has far reaching implications, perhaps the most poignant being that of creating hospitable spaces for Indigenous students. This study will seek to understand the ways in which Indigenous students perceive a sense of hospitality in their school ecologies, as well as examine the ways in which a sense of true hospitality might be fostered in school settings for and by Indigenous students. Through examining physical spaces, curriculum, and social relations in schools, the notion of hospitality will be utilized to bring forth both critiques as well as recommendations for school systems and structures to become hospitable to Indigenous students.

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)0.004
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 score0.904
Threshold uncertainty score0.191

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0150.021
Scholarly communication0.0100.005
Open science0.0010.012
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.240
Teacher spread0.222 · 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
Published2023
Admission routes1
Has abstractyes

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