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Record W6980385677

Canadian Post-secondary Institutional Response to Students’ Off-campus Behaviour

2021· dissertation· W6980385677 on OpenAlexfundaboutno aff

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldHealth Professions
TopicMaternal and Neonatal Healthcare
Canadian institutionsnot available
FundersBritish Columbia Institute of TechnologyThompson Rivers UniversityOffice of International Science and EngineeringKwantlen Polytechnic UniversityBrigham Young University
KeywordsMisconductLegitimacyContext (archaeology)AccountabilityScope (computer science)Key (lock)Qualitative research
DOInot available

Abstract

fetched live from OpenAlex

This study sought to explore how Canadian post-secondary institutions [CPIs] address students’ off-campus behaviours [OCBs]. Findings were generated through document analysis of 41 Student Codes of Conduct [SCCs], an examination of four relevant illustrative cases, and semi-structured interviews with five CPI administrators responsible for student discipline. These three sources were then triangulated for further analysis and consideration of key research questions. My original contribution to the research phenomenon is to present an informed understanding of how SCCs are used at CPIs in the context of five participating institutional key informants’ responses to incidents of student OCBs. This research also examined the legitimacy and authority of CPIs institutional responses to alleged instances of student misbehaviour which occur off-campus in four illustrative case studies.Key findings revealed that SCCs varied widely in terms of their scope and authority. While some do acknowledge OCBs as meriting administrative response, a clear connection to the CPI is needed to enact such a response. In the illustrative case studies this was also seen in how the CPI administrators determined how and when to respond to students’ OCBs. Interviews with key informants echoed this need to determine each act of misconduct as a standalone case and to determine best outcomes with taking what external parties may view as extreme measures. In all three data sets, specific processes of progressive discipline were taken to enforce ‘perceived’ fairness for all parties involved. The four illustrative cases also highlighted both the use of SCCs and the administrative response to students’ OCBs in that procedural fairness is not always framed in the same manner nor are policies implemented with universal use in that policy revision and reimplementation is often incited by significant occurrences of student misconduct. As such, consideration was given to the cyclical nature of policy design and implementation in addressing the research phenomenon. Implications of the findings include a consideration of additional areas of research study such as meta-analysis of SCCs, intersectionality of CPI administrators and potential expansion of scope and authority of CPIs as online and remote learning expands.

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)0.006
metaresearch head score (Gemma)0.018
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 score0.927
Threshold uncertainty score0.532

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0170.006
Scholarly communication0.0060.001
Open science0.0020.006
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 head0.038
GPT teacher head0.454
Teacher spread0.416 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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