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Record W4250396041 · doi:10.32920/ryerson.14655645.v1

Information exchange : the effect of new information typologies on library architecture

2021· preprint· en· W4250396041 on OpenAlexaffabout
Mark Lawrence Friesner

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicLibrary Science and Administration
Canadian institutionsToronto Metropolitan UniversityUniversity of Manitoba
Fundersnot available
KeywordsArchetypeArchitectureSpace (punctuation)World Wide WebInfillLibrary scienceComputer scienceDigital libraryQUIETArchitectural engineeringEngineeringHistoryArchaeologyCivil engineeringArt

Abstract

fetched live from OpenAlex

This thesis document investigates contemporary forms of information media and their effects on library architecture. The reseach portion of this document concludes with a design project that illustrates a solution to programmatic infill imposed upon academic libraries built prior to the rise of digital media. The casualties of injecting additional porgram elements into older libraries are the print collections. Many such libraries have adopted roles resembling community centres and have lost space devoted to quiet study and book stacks. The driving concept for this project was to return the program of the Ryerson University Libary to a state closer to its original design. By reintroducing lost collections and quiet work areas, the interactive and digitial program elements are forced outside the walls of the original building. This expelled program has been reformatted into a new archetype and is skinned as such, creating an additional university building focused on information exchange.

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)0.014
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0070.014
Scholarly communication0.0270.034
Open science0.0020.015
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.001

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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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 designObservational
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
Published2021
Admission routes2
Has abstractyes

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