MétaCan
Menu
Back to cohort
Record W3210456005 · doi:10.32920/ryerson.14665872.v1

Spatial effects : narrative structure in architecture

2021· preprint· en· W3210456005 on OpenAlexaff
Nadia Qadir

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNarrativeArchitectureTypologyMovie theaterNarrative structureSpace (punctuation)Dominance (genetics)HistoryNarrative networkFunction (biology)LiteratureAestheticsNarrative inquiryVisual artsArtLinguisticsNarrative criticismPhilosophyArchaeology

Abstract

fetched live from OpenAlex

The potency of compelling narrative structures - or the story constructing sequence of space - has pushed architecture's boundaries into new frontiers through the development of representational technology such as cinema, a burgeoning art form that employs narrative typology as an underlying structure to frame the phenomena of space. In this design research thesis my intention is to investigate and elucidate the function and purpose of narrative in Architecture and Cinema and its development from symbolism to spatial formation. Thesis statement: The first stage of narrative from took flight from pictographic symbols and cartographic delineations to sculptural representations and reliefs. These timeless narratives encapsulated in monumental structures such as the Pyramids of Giza or the Greek Parthenon depict their civilizations' cultural dominance through this system of messaging. It can be argued that a number of such illustrations may reveal varying levels of codification or messaging through historical, cultural, or religious contexts. However, the present form of this system of messaging and symbolism has been considerably altered for the worse, becoming banal and superficial, and lacking depth and narrative content.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.009
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0010.001
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 head0.004
GPT teacher head0.184
Teacher spread0.180 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicUrban Design and Spatial AnalysisFrench-language works237,207