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Record W3154971897

Contemplating Infrastructure: An Ethnographic Study of the University of Toronto Faculty of Information Inforum’s iRelax Mindfulness Resource Area

2021· dissertation· en· W3154971897 on OpenAlexfundaboutno aff
Hugh Kevin Samson

Bibliographic record

VenueTSpace · 2021
Typedissertation
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsMindfulnessEthnographyResource (disambiguation)SociologyInformation resourceLibrary sciencePsychologyKnowledge managementPsychotherapistAnthropologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Created in 2016, the iRelax area is an innovative meditation and yoga resource hub situated within the University of Toronto Faculty of Information’s Inforum. Comprised of approximately fifty interconnected digital, physical, and textual resources, the iRelax area possesses a distinctly open and visible spatial profile intended to promote open conversations about mental health. This ethnographic case study of the iRelax area examines the initiative’s aesthetic, informational, organizational, and spatial properties, as well as individuals’ encounters and interactions therewith. The iRelax area’s associated Mindful Moments program, or free, guided meditation sessions offered within the learning commons one day per week, is also examined. In order to develop a detailed understanding of the relationship between the iRelax area and this program, the study’s design was broadened to include consideration of contemplative inquiry as a complement to ethnography. The study casts the iRelax area and its associated Mindful Moments program as contemplative infrastructure.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.139
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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 teacher head, 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
Published2021
Admission routes2
Has abstractyes

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