MétaCan
Menu
Back to cohort
Record W2752647297 · doi:10.1177/1359183517729428

An order of distinction (or, how to tell a collection from a hoard)

2017· article· en· W2752647297 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Material Culture · 2017
Typearticle
Languageen
FieldPsychology
TopicBody Image and Dysmorphia Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsHoarding (animal behavior)HoardEthnographyObject (grammar)Order (exchange)Set (abstract data type)SociologyParticipant observationEpistemologyAestheticsMedia studiesHistorySocial scienceAnthropologyArchaeologyArtEcologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

What is the difference between a collection and a hoard? This article draws upon an array of sources – from the DSM-V and current psychiatric research on hoarding, to recent media stories and artist Song Dong’s Waste Not (2009), to the author’s own participant observation with the Toronto Hoarding Coalition and the 21 ethnographic interviews she conducted with professional home organizers in the Greater Toronto Area between 2014 and 2015 – to examine how popular and psychiatric discourses that distinguish collecting and hoarding reveal a complex set of rules about what constitutes the healthy and moral ordering, organization and arrangement of one’s material possessions in contemporary life. In an age of seemingly limitless possibilities for accumulation, the author argues that it is not just the fact of having things that stands as a matter of distinction. One must also demonstrate an active engagement in practices related to the curation and management of one’s object world.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.678
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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