MétaCan
Menu
Back to cohort
Record W2923813122

Cultural infrastructure, public space, and the contemporary library in Toronto

2017· article· en· W2923813122 on OpenAlexaboutno aff
Zoë Ritts

Bibliographic record

VenueDigital Commons - RISD (Rhode Island School of Design) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsPublic spaceSpace (punctuation)Media studiesSociologyPolitical scienceGeographyArchitectural engineeringEngineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

Public space is an aggregate of differences, a place of exposure and adjacency to other lived social realities. The potential of public space is the confrontation or mediation of differences through interaction. Public spaces are therefore about intersections and visual transparency between publics. Through architecture, we can create the conditions for contact with difference: with openness, transparency, density of program, and merging and splitting trajectories, we can work toward greater engagement in society. As civic institutions, the bus station, an affordable method of transportation and movement, and the library, a crucial component of cultural infrastructure, can collide to create a space that sites this social exchange – centered around dialogue. Busses are an inexpensive method of transportation, and are thus used by publics with little access to other means of more ‘hermetic’ travel. Similarly, libraries have evolved beyond an ‘archive’ model to a new type of node in an information network, a place where the dissolving components of knowledge and media are centrally accessible.

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 score0.167
Threshold uncertainty score0.966

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0270.013
Scholarly communication0.0110.003
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.047
GPT teacher head0.302
Teacher spread0.255 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDigital Commons - RISD (Rhode Island School of Design)Same topicLibrary Science and AdministrationFrench-language works237,207