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Record W2762109535 · doi:10.15173/ijsap.v1i2.3092

The Opening Conference: A Case Study in Undergraduate Co-design and Inquiry-based Learning

2017· article· en· W2762109535 on OpenAlexvenueno aff
Zak Rakrouki, Mark Gatenby, Stefan Cantore, Thomas Rowledge, Tom Davidson

Bibliographic record

VenueInternational Journal for Students as Partners · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Learning designSpace (punctuation)Higher educationEvent (particle physics)PedagogySociologyAcademic communityMathematics educationEngineering ethicsEngineeringPolitical sciencePsychologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

The separation between “research” and “teaching” in universities has been under increasing challenge from scholars who want to place inquiry-based learning at the centre of higher education. An important approach to challenging established paradigms and structures is to question, and thereby destabilise, role distinctions, relationships, language, and learning spaces. In this article we present a case study of a conference organized in collaboration between staff and students for first-year undergraduates. Reinventing the academic conference space is our aim in challenging assumptions about undergraduate education. As co-designers of the conference, we reflect on the activities and institutional context leading to the creation of the event, its design and implementation, and its impact on the undergraduate learning community.

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)0.021
metaresearch head score (Gemma)0.042
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 score0.023
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.042
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0230.013
Scholarly communication0.0110.007
Open science0.0050.012
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0050.001

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 head0.210
GPT teacher head0.658
Teacher spread0.449 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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