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Record W7116598550

Provenanced Aesthetics. The Beauty of Decay in Dawson City: Frozen Time

2025· article· en· W7116598550 on OpenAlexvenueno aff
Patrick Keilty

Bibliographic record

VenueArchivaria · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsnot available
Fundersnot available
KeywordsMovie theaterEphemeral keyConversationMeaning (existential)BeautyRationalization (economics)
DOInot available

Abstract

fetched live from OpenAlex

Cinema is critical to our understanding of modern archives. Hailed as the permanent record of fleeting moments, cinema emerged at the turn of the 20th century as an unprecedented form of archival knowledge, even as it represented a form of ephemerality in the face of modernity’s increasing rationalization and standardization within archives. So, why are archival studies and cinema studies not in greater conversation with each other? This article allows for a cross-pollination of rigorous methodological and theoretical approaches from cinema studies to add new dimensions to archival theory. Through a close reading of sound, material decay, and film editing, this article argues that Dawson City: Frozen Time reflects the historical symmetry between cinematic and archival impulses to capture the ephemeral while grappling with the material limits of preservation. Dawson City: Frozen Time turns decay into an archival aesthetic not only to convey the way archival records gain meaning when viewed in relation to their unstable custodial histories but also to demonstrate the finitude and distortion of memory and history. Indeed, Dawson City: Frozen Time reframes archives as sites of creative irruption and, specifically, of decay and provenance as aesthetic contrivances that remind us of history’s instability.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.992
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.022
Scholarly communication0.0120.008
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.014
GPT teacher head0.206
Teacher spread0.191 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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