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Record W2142006627 · doi:10.1017/s1060150314000035

“NOT ALTOGETHER UNPICTURESQUE”: SAMUEL BOURNE AND THE LANDSCAPING OF THE VICTORIAN HIMALAYA

2014· article· en· W2142006627 on OpenAlexaff
Sandeep Banerjee

Bibliographic record

VenueVictorian Literature and Culture · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsGlacierMode (computer interface)IdeologyArtHistoryArt historyRelation (database)GeographyArchaeologyPhysical geographyPolitics

Abstract

fetched live from OpenAlex

During his third expedition into the higher Himalaya in 1866, the most ambitious of his three journeys into the mountains, Samuel Bourne trekked to the Gangotri glacier, the source of the Ganges. At that site he took “two or three negatives of this holy and not altogether unpicturesque object,” the first photographs ever made of the glacier and the ice cave called Gomukh, meaning the cow's mouth, from which the river emerges (Bourne 96). These words of Victorian India's pre-eminent landscape photographer, importantly, highlight the coming together of the picturesque mode and the landscape form through the medium of photography. In this essay, I focus on Samuel Bourne's images of the Himalaya, produced between 1863 and 1870, to query the ideological power of this triangulation to produce a specific image of the mountains in late nineteenth-century Victorian India. Situating Bourne's images in relation to contemporaneous material practices of the British within the space of the Himalaya, namely, the establishment of hill stations as picturesque locales in the higher altitudes of the Indian subcontinent, I argue that the landscape form, the picturesque mode, and the photographic medium, inflect each other to tame the sublimity of the mountains by representing them as similar to the Alps.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.252
Teacher spread0.246 · 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
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

Citations3
Published2014
Admission routes1
Has abstractyes

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