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Record W3102643357 · doi:10.22215/etd/2020-14265

Symbols, Sentinels and Reading Rooms: Cultivating Literacies of Place in Central Industrial, Saskatoon

2020· dissertation· en· W3102643357 on OpenAlexaboutno aff
Kevin Complido

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretation (philosophy)Reading (process)ArchitectureSemioticsStorytellingSense of placePerspective (graphical)Architectural engineeringSociologyIdentity (music)Work (physics)Industrial heritageVisual artsCultural heritageHistoric siteMedia studiesAestheticsEngineeringCultural heritage managementPolitical scienceGeographyCivil engineeringNarrativeArchaeologyArtEpistemologySocial scienceComputer scienceLiterature

Abstract

fetched live from OpenAlex

The purpose of this thesis is to promote a perspective of architectural evolution centred on heritage interpretation and its spatial representations, driven by matters of values, identity, and local history. This work suggests novel site analysis methodologies based on frameworks borrowed from storytelling, semiotics, and photography, working towards the design and development of 'Symbols, Sentinels and Reading Rooms' for the site. Findings and approaches orbit around ongoing, timely proposals for a new public library and architecture school, imagining conservation and its representations as facilitators of a public's sense of a 'co-created' place. As an exploratory project, the work argues that heritage conservation, in practices of design and planning, is an overlooked force in its capacity to foster and sustain relationships with the public. 'Cultivating Literacies of Place' strives¬ to make Central Industrial's spirit of place known—the site's atemporal stories, visual language, and the interpretation of heritage.

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)0.002
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 score0.861
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.010
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.107
GPT teacher head0.255
Teacher spread0.148 · 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
Published2020
Admission routes1
Has abstractyes

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