MétaCan
Menu
Back to cohort
Record W1820063639

Teaching a 'Humanistic' Science: Reflections on Interdisciplinary Course Design at the Post-Secondary Level

2011· article· en· W1820063639 on OpenAlexaffabout
Marcia Jenneth Epstein

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2011
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCourse (navigation)HumanismMathematics educationPedagogyHumanistic educationEngineering ethicsPsychologySociologyEngineeringPhilosophyTheology
DOInot available

Abstract

fetched live from OpenAlex

Development of post-secondary curriculum in emerging interdisciplinary fields presents particular challenges in course design and resource utilization, especially when the field is interdisciplinary by nature of its inherent breadth. A new course at the University of Calgary, designed to introduce undergraduate students to the methods and philosophy of Acoustic Ecology --- the study of sound and its effects on health, cognition and culture -- exemplifies both the challenges and some practical solutions. Following a brief history of the concept and its philosophy, a summary and critique is presented from the first offering of the course as a pilot project. Conclusions drawn include the necessity of an integrative approach to interdisciplinary fields of study that are true 'interdisciplines', the utility of experiential fieldwork, and the advantages presented by a student group with diverse academic backgrounds.

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)0.066
metaresearch head score (Gemma)0.081
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 score0.066
Threshold uncertainty score0.349

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0180.012
Scholarly communication0.0160.005
Open science0.0050.012
Research integrity0.0060.010
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 head0.699
GPT teacher head0.675
Teacher spread0.024 · 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
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicInterdisciplinary Research and CollaborationFrench-language works237,207