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Record W2808120738 · doi:10.15273/jue.v2i1.8117

Opening Doors and Sitting on Floors: Public Events in Private Spaces: the (re)-appropriation of space through grassroots events in Halifax

2012· article· en· W2808120738 on OpenAlexaffvenueabout
Samantha Levy, Susannah Church

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsDalhousie University
Fundersnot available
KeywordsAppropriationGrassrootsDoorsPublic spaceEvent (particle physics)Space (punctuation)Session (web analytics)Boundary (topology)Public relationsSociologyMedia studiesPolitical scienceAdvertisingEngineeringBusinessArchitectural engineeringPoliticsComputer scienceLaw

Abstract

fetched live from OpenAlex

As a group of university students, we came together to discuss social trends we had noticed around our respective neighbourhoods in Halifax. We set out to investigate public events in private spaces. We found that these private spaces included the backyards and living rooms of those hosting the events. We focused on four case studies, which included an open-mic show, an art show, a lecture series event and a story-telling session to gather our research. It appears that this trend represents a need for a greater sense of community within our city and an outlet to share creative projects and ideas. The concept of blurring the boundary between public and private spaces is indicative of greater social support within an urban 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)0.001
metaresearch head score (Gemma)0.002
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 score0.805
Threshold uncertainty score0.388

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.013
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.433
GPT teacher head0.549
Teacher spread0.117 · 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

Citations2
Published2012
Admission routes3
Has abstractyes

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