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The times of the curator

2019· book-chapter· en· W4234649512 on OpenAlexaboutno aff
James Clifford

Bibliographic record

VenueManchester University Press eBooks · 2019
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalitiesIndigenousIdeologyHistorySkepticismGlobalizationAestheticsSociologyArtPoliticsEpistemologyPolitical sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

The museum is an inventive, globally and locally translated form, no longer anchored to its modern origins in Europe. Contemporary curatorial work, in these excessive times of decolonisation and globalisation, by engaging with discrepant temporalities—not resisting, or homogenising, their inescapable friction—has the potential to open up common-sense, ‘given’ histories. It does so under serious constraints—a push and pull of material forces and ideological legacies it cannot evade. This chapter explores the ‘times’ of the curator, both in terms of these <italic>times</italic> we live in, in which curatorial theory and practice seems to be ever-present, and a sense of the curator’s task as enmeshed in multiple, overlapping, sometimes conflicting <italic>times</italic>. It is concerned primarily with the later, the discrepant temporalities, or perhaps that should be ‘histories’, or even ‘futures’, that are integral to the task of the curator today. In contrast to the history of museum curating, curatorial work in recent years has been transformed by the re-emergence of indigenous cultures in former settler colonies which suggest the de-centering of the west. Drawing on research in the USA, Canada and the Pacific Islands, and analysing several diverse case studies and examples, the chapter explores examples of ‘indigenous curating’, that is to say, working with things and relations in transforming <italic>times</italic>. In doing so, it contributes to a world-wide debate, which this book is part of, about museums and the future of curatorship.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.981
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.167
Teacher spread0.136 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2019
Admission routes1
Has abstractyes

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