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Record W3160901105 · doi:10.15027/50767

カナダの大学における学生支援の展開とその特徴 : CACUSS(Canadian Association of College and University Student Services) の取り組みに注目して

2021· article· ja· W3160901105 on OpenAlexaboutno aff
Shinichi Cho

Bibliographic record

VenueHiroshima University Acedemic Information Repository (Hiroshima University) · 2021
Typearticle
Languageja
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsAssociation (psychology)Medical educationHigher educationMathematics educationPolitical sciencePsychologyMedicine

Abstract

fetched live from OpenAlex

This paper examines the development and characteristics of student affairs services in Canadian universities. Compared to our understanding of student affairs services in the United States context, no previous research has focused specifically on student affairs services in Canada, and the professional organization of these services and related activities have never undergone basic analysis. Thus, this paper is based on newly identified primary evidence acquired by the author from the CACUSS Office Secretariat in Canada, the analysis of which leads to the following conclusions. First, after I provide an overview of the history of the organization, I analyze two CACUSS primary documents: “The Mission of Student Services” (1989) and “CACUSS Student Affairs and Services Competency Model English” (2016). Second, I consider the creation process of “CACUSS Student Affairs and Services Competency Model English” (2016). Notably, the CACUSS refer to student affairs services documents published by American professional organizations (e.g. ACPA, NASPA, and ACUHO-I). In light of these results, the basic viewpoints of student affairs services in the Canadian context are shown.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0030.000
Scholarly communication0.0000.004
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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 designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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