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Record W2344327469 · doi:10.1080/10509585.2016.1163789

Human Objects, Object Rights: from Elgin’s Marbles to Bullock’s Laplanders

2016· article· en· W2344327469 on OpenAlexaff
Sophie Thomas

Bibliographic record

VenueEuropean Romantic Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsExhibitionMerge (version control)Object (grammar)RomancePoliticsSociologyUncannyAestheticsVisual artsLawArtPhilosophyLiteratureComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This essay probes the question of rights along the porous boundary between persons and things. Its broader framework is the rapid expansion of museums – and museum collections – in the Romantic period, but it examines in particular two episodes that in different ways mingle and merge bodies and objects. The first is the still-controversial acquisition of marbles from the Parthenon by Lord Elgin, and their subsequent sale to the British Museum. The complex debates surrounding this transaction are ethical, political, and aesthetic in nature, but what is of interest here is the emphasis, on the part of contemporary commentators, on the uncanny life-likeness of the fragments. The second part of the essay considers this problem from another angle by examining William Bullock’s temporary exhibition, at his London Museum in 1822, of a family of Laplanders, their reindeer and sleds, and examples of their cultural and domestic artifacts. Body-object, object-body: this inversion, so resonant now in a critical climate engaged by thing theory and object oriented ontologies, takes on additional force in the emergent cultural economy of the Romantic museum, where the right to (and of) the object, and the place of the body, are provocatively on display.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0030.015
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0030.002
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 head0.029
GPT teacher head0.319
Teacher spread0.290 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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