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Record W4323644940 · doi:10.1080/14629712.2023.2173410

Elizabeth I, Huntress of England: Private Politics, Diplomacy, and Courtly Relations Cultivated through Hunting

2023· article· en· W4323644940 on OpenAlexaff
Dustin M. Neighbors

Bibliographic record

VenueThe Court Historian · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Art and Culture Studies
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsPoliticsEliteDiplomacyEphemeral keySociologyPolitical scienceEthnologyLaw

Abstract

fetched live from OpenAlex

Hunting at the court of Elizabeth I of England was not a peripheral activity, nor was it a solely male pursuit. Hunting was an important social and cultural practice that was pivotal for communication, gathering information, social intercourse and politics. At the same time, hunting was an informal and ephemeral activity that was secluded and offered degrees of privacy. Yet the study of hunting as a contextually and culturally driven phenomenon that straddled the public/private divide, as an activity where elite women were active agents and skilled huntresses, and how these dimensions impacted early modern sociability, court culture, politics, and diplomacy remains underexplored. To begin addressing this gap, this article demonstrates how Elizabeth I not only regularly engaged in hunting, but also maintained a dedicated hunting staff and utilised hunting as a tool to facilitate private politics and shape courtly behaviour.

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 score0.120
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0140.019
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.244
Teacher spread0.216 · 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
Published2023
Admission routes1
Has abstractyes

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