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Record W7033909775

A Study of Photography and Walking through the City in Modern,
\nPostmodern, and Contemporary Canadian Art

2012· dissertation· en· W7033909775 on OpenAlexfundaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2012
Typedissertation
Languageen
FieldArts and Humanities
TopicPublishing and Scholarly Communication
Canadian institutionsnot available
FundersConcordia University
KeywordsPhotographyMeaning (existential)Space (punctuation)Urban spacePhotojournalismContemporary art
DOInot available

Abstract

fetched live from OpenAlex

The connection between photography and walking is fundamental in the history of Canadian photography and art.This association has not garnered any significant study until now, although its presence can be seen increasing in various forms of photographic works since the middle of the twentieth century.Theoretical approaches dealing with place and space support analysis of realist photographs and conceptual projects where this combination is represented, intentionally or factually.Boulevard Saint-Laurent, in Montreal, provides a historic place and cultural space, as well as the site and surface for the creation of an original artwork, Every Foot of the Sidewalk: boulevard Saint-Laurent (2010-2012.Interviews with significant Canadian photographers and artists related to questions of urban space, walking, photography and art history are conducted to understand better the importance and meaning of this combined activity, and these interviews are analyzed in the text.This thesis explains the bond between photography and walking over the last half century, confirming its force as a continued source of inspiration for contemporary photographers and artists, in Canada and elsewhere.1 Tom Gibson, "A Conversation with Tom Gibson, Annotated by Martha Langford," in False Evidence Appearing Real (Ottawa: CMCP, 1993), 97.

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)0.004
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 score0.062
Threshold uncertainty score0.450

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0290.020
Scholarly communication0.0070.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.072
GPT teacher head0.278
Teacher spread0.206 · 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
Published2012
Admission routes2
Has abstractyes

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