MétaCan
Menu
Back to cohort
Record W2157773946 · doi:10.1123/ssj.2012-0179

Teaching Across the Lines of Fault in Psychology and Sociology: Health, Obesity and Physical Activity in the Canadian Context

2014· article· en· W2157773946 on OpenAlexaffabout
Fiona J. Moola, Moss E. Norman, LeAnne Petherick, Shaelyn M. Strachan

Bibliographic record

VenueSociology of Sport Journal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSociologyContext (archaeology)DilemmaIdeologyEpistemologySpace (punctuation)KinesiologySet (abstract data type)Social sciencePoliticsMedicinePolitical science

Abstract

fetched live from OpenAlex

While interdisciplinary knowledge is critical to moving beyond categorical ways of knowing, this comes with its own set of pedagogical challenges. We contend that acknowledging existing knowledge hierarchies and epistemological differences, recognizing the ideological baggage that students’ bring to the classroom in terms of their understandings of health, embracing intellectual uncertainty, and encouraging learning-as-witnessing, are fundamental to fostering an interdisciplinary pedagogy that opens up a space for dialogue between psychology and sociology. We draw on the case of obesity and physical inactivity in the Canadian context as an exemplar of a kinesiology dilemma in which both psychology and sociology have important, albeit different, roles to play. We suggest that the anxiety provoked by such an approach is not only necessary but productive to forge an intellectual space where psychologists and sociologists may better hear one another.

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)0.011
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 score0.140
Threshold uncertainty score0.997

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0580.057
Scholarly communication0.0140.005
Open science0.0030.010
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.389
Teacher spread0.357 · 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

Citations5
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueSociology of Sport JournalSame topicSocial and Cultural DynamicsFrench-language works237,207