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Record W3187518365 · doi:10.17533/udea.ef.n64a03

No maps for these territories: exploring philosophy of memory through photography

2021· article· en· W3187518365 on OpenAlexaff
Alun C. Kirby

Bibliographic record

VenueEstudios de Filosofía · 2021
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsSNC-Lavalin (Canada)
FundersArts Council England
KeywordsMnemonicPhotographyPerceptionEpisodic memoryCultural memoryAutobiographical memoryKey (lock)Cognitive sciencePsychologyCognitive psychologyVisual artsAestheticsComputer scienceSociologyArtCognitionRecallAnthropology

Abstract

fetched live from OpenAlex

I begin by examining perception of photographs from two directions: what we think photographs are, and the aspects of mind involved when viewing photographs. Traditional photographs are shown to be mnemonic tools, and memory identified as a key part of the process by which photographs are fully perceived. Second, I describe the metamorphogram; a non-traditional photograph which fits specific, author-defined criteria for being memory. The metamorphogram is shown to be analogous to a composite of all an individual’s episodic memories. Finally, using the metamorphogram in artistic works suggests a bi-directional relationship between individual autobiographical memory and shared cultural memory. A model of this relationship fails to align with existing definitions of cultural memory, and may represent a new form: sociobiographical memory. I propose that the experiences documented here make the case for promoting a mutually beneficial relationship between philosophy and other creative disciplines, including photography.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.026
Scholarly communication0.0060.013
Open science0.0010.003
Research integrity0.0010.003
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 head0.188
GPT teacher head0.316
Teacher spread0.127 · 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
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

Citations1
Published2021
Admission routes1
Has abstractyes

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