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Record W3199444004 · doi:10.32920/ryerson.14663679.v1

“NOT IMPORTANT” : an analysis of the Tibet photo service medium format negatives at the Tibet Museum

2021· preprint· en· W3199444004 on OpenAlexaff
Lodoe-Laura Haines-Wangda

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNegativeArchivistService (business)StudioVisual artsComponent (thermodynamics)DirtArticulation (sociology)InstitutionLibrary sciencePoliticsSociologyGeographyArtComputer scienceCartographyPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

This thesis approaches a body of 1,428 6x6 cm gelatin silver acetate negatives in the Tibet Museum’s photographic archives in Dharamsala, India. This material, labelled “not important” by an archivist at their collecting institution, contains images of the Tibetan community in exile, made by the Tibet Photo Service (TPS) studio between 1962 and 1987. The practical component of this project involves arranging and rehousing the negatives for accessibility and preservation purposes. The theoretical component of this project provides a contextual framework for the TPS medium format negatives, unpacking the reasons behind their exclusion from care and display. Additionally, it engages the negatives as sites of “articulation and aspiration” of the Tibetan exile community. The objects and their images are recontextualized from material that is “not important” to social and political documents that serve as a subjective historical record of the foundational years of the Tibetan community in India.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.004
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.098
GPT teacher head0.261
Teacher spread0.163 · 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
Published2021
Admission routes1
Has abstractyes

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