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Record W2528918640 · doi:10.3366/anh.2016.0380

A vile passion for altering names: the contributions of Charles Thorold Wood jun. and Neville Wood to ornithology in the 1830s

2016· article· en· W2528918640 on OpenAlexaff
T. R. Birkhead, Robert Montgomerie

Bibliographic record

VenueArchives of Natural History · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsQueen's University
Fundersnot available
KeywordsOrnithologyBrotherPraisePassionClassicsHistoryArt historyArtLiteratureSociologyAnthropologyBiologyEcologyPsychologySouthern Hemisphere

Abstract

fetched live from OpenAlex

During the 1830s, Charles Thorold Wood jun. and his younger brother Neville Wood, published, separately, three books and a series of articles dealing with two ornithological subjects: the common and scientific names of birds, and the cataloguing of publications. Probably following William Swainson's lead, the Woods were enthusiastic about standardizing the common (English) bird names and making them logical and meaningful. They also each published an annotated bibliography of ornithological publications, notable for being among the first of such compilations, but also for the vitriol with which they criticized those – James Rennie and Hugh Strickland, in particular – whose work they did not like. In contrast, the praise they heaped on those they did approve of – William Swainson, John Latham, Robert Mudie, Prideaux John Selby, Francis Willughby and each other – was excessive. Possibly because of the tenor of their comments about other ornithologists, and the strangeness of their proposed English bird names, the Woods’ work has rarely been cited, and their new names for birds were virtually ignored from the start.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.653

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 science0.0000.000
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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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 designBench or experimental
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

Citations2
Published2016
Admission routes1
Has abstractyes

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