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Record W4248353577 · doi:10.47678/cjhe.v48i1.187971

Resource Centre or Experience Desk? The Spatiality of Services to Indigenous and International Students at Universities in Ontario, Canada

2018· article· en· W4248353577 on OpenAlexaffvenueabout
Jean Michel Montsion

Bibliographic record

VenueCanadian Journal of Higher Education · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsYork University
Fundersnot available
KeywordsDeskIndigenousMainstreamContext (archaeology)Space (punctuation)SociologyPoliticsResource (disambiguation)Public relationsWork (physics)Service (business)Higher educationPolitical scienceLibrary scienceGeographyBusinessMarketingEngineeringEcology

Abstract

fetched live from OpenAlex

In recent years, Ontario universities have increasingly targeted Indigenous and international students for recruitment. Focusing on three southern Ontario universities, I examine how service delivery for these student groups is organized in space. In light of Henri Lefebvre’s work, I argue that the spatiality of the information hubs created to support them differs significantly, each being defined in the interactions between institutional assumptions about the student group, the social presence and activities hosted, and the lived experiences of the students utilizing these services. Whereas Indigenous student services are organized as a resource centre to create a separate space for Indigeneity on campuses, international student services take the form of an experience desk to emphasize rapid integration into the mainstream. Based on interviews with students and staff, I reflect on the differences between the two models to discuss the spatial politics of information hubs within the context of Ontario universities.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.327
Teacher spread0.300 · 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 teacher head, not a consensus.

Study designObservational
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

Citations5
Published2018
Admission routes3
Has abstractyes

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