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Record W2758537031 · doi:10.18833/spur/1/1/2

Undergraduate Research and Student-Staff Partnerships: Supporting the Development of Student Scholars at a Canadian Teaching and Learning Institute

2017· article· en· W2758537031 on OpenAlexafffundabout
Elizabeth Marquis

Bibliographic record

VenueScholarship and Practice of Undergraduate Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsMathematics educationPedagogyUndergraduate researchPsychologyMedical educationMedicine

Abstract

fetched live from OpenAlex

Undergraduate research and inquiry and student-staff partnerships in teaching and learning have much in common, although their connections are not often discussed explicitly.Partnership initiatives-particularly those that engage students in collaborating with faculty/staff on disciplinary research or the scholarship of teaching and learning-share many features with undergraduate research efforts, including the potential to help students develop as active and engaged producers and scholars.Building on these connections, this article describes a unique 'student partners program' housed within the teaching and learning institute at McMaster University (Canada) considering its role in the development of outcomes desired by scholars and practitioners of undergraduate research and student-staff partnership.This assessment can assist in further consideration of the place of partnership within undergraduate research.

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)0.033
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.041
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0400.013
Scholarly communication0.0140.004
Open science0.0070.028
Research integrity0.0040.007
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 head0.368
GPT teacher head0.544
Teacher spread0.177 · 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.

Study designQualitative
DomainIncentives
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

Citations10
Published2017
Admission routes3
Has abstractyes

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