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Record W7132863904

Spatial Agency: A Temporal and Physical Museological Exploration

2020· dissertation· W7132863904 on OpenAlexaboutno aff
Andrea Blanca Cisneros Popoca

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldSocial Sciences
TopicSpatial and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSpace (punctuation)Agency (philosophy)Spatial contextual awarenessSpatial relationAssemblage (archaeology)Spatial analysisValue (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

This research paper presents the observation of spatial agencies by exploring three different archaeological sites and their museums; the Toniná Site Museum in Mexico, the Archaeological Museum and Roman Fish Salting Factory in Spain, and L'Anse aux Meadows National Historic Site in Canada. Spatial agency is understood as the power that space exercises in humans and non-humans. This thesis demonstrates that it is possible to understand space through museological observation and data collection. This analysis examines the factors that make spatial relations unique and compares them from one museum to another. Spatial agencies are found to be expressed through human and non-human interactions that differ locationally. Spatial Agency: A Temporal and Physical Museological Exploration argues that value can be found in questioning space though its own rules. This thesis offers an approach to how spaces should be critically examined according to the lived experiences of inhabiting them.

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)0.004
metaresearch head score (Gemma)0.005
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0070.016
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0010.001
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 head0.069
GPT teacher head0.374
Teacher spread0.304 · 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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