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Record W2332484471 · doi:10.2304/plat.2013.12.1.83

Organizing an Undergraduate Psychology Conference: The Successes and Challenges of Employing a Student-Led Approach

2013· article· en· W2332484471 on OpenAlexaffabout
Cory L. Pedersen, Jocelyn Lymburner, Jordan I. Ali, Patricia I. Coburn

Bibliographic record

VenuePsychology Learning & Teaching · 2013
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsKwantlen Polytechnic University
Fundersnot available
KeywordsPerspective (graphical)Graduate studentsUndergraduate educationEvent (particle physics)PsychologyMedical educationPedagogySociologyMedicineComputer science

Abstract

fetched live from OpenAlex

Connecting Minds (CM) is a North American undergraduate research conference in psychology, hosted annually by Kwantlen Polytechnic University in British Columbia, Canada. However, CM is a conference with a twist: it is both student-focused and student-led. The organizing committee is comprised of both faculty and students working collaboratively. While prone to some unique challenges, this approach to conference organization has been exceedingly successful, both for the event and the individuals involved. The organization of CM provides an opportunity for faculty to take teaching out of the classroom, and for students to develop skills essential for success at the graduate level of their education or in employment settings. This article presents the challenges and benefits intrinsic to such a model from both a faculty and student perspective.

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)0.069
metaresearch head score (Gemma)0.067
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0690.067
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.006
Scholarly communication0.0190.005
Open science0.0050.013
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0030.002

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 head0.053
GPT teacher head0.373
Teacher spread0.320 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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