MétaCan
Menu
Back to cohort
Record W4214809773 · doi:10.25071/2561-5467.286

Moses Perley and the Fisheries

2013· article· en· W4214809773 on OpenAlexvenueno aff
William G. Welch

Bibliographic record

VenueThe Northern Mariner / Le marin du nord · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Auteur, naturaliste, homme d'affaires et avocat -ainsi que fonctionnaire -Moses Henry Perley était un personnage familier en Amérique du Nord britannique et au-delà, il y a un siècle et demi.Plus intéressant pour nous aujourd'hui, cependant, sont ses liens avec les pêcheries.En tant qu'observateur et journaliste, Perley a amoncelé des renseignements sur les pêcheries du dixneuvième siècle.Son rôle dans l'histoire de la pêche -en particulier les négociations pour régler les différends avec les États-Unis dans les années 1850 -est l 'objet de cet essai.An author, a naturalist, a businessman and a lawyer -as well as a public official -Moses Henry Perley was a familiar figure in British North America and beyond a century and a half ago.Of more interest to us today, however, are his connections with the fisheries.As an observer and reporter, Perley generated a wealth of information on the nineteenth-century fisheries.His role in the history of the fisheries is the subject of the following essay.Perley was born in New Brunswick in 1804, his family having been part of the great Yankee migration "down-east" that attended the end of the French and Indian wars.Close-knit and prolific, the Perleys were of ancient lineage in their native New England, and, throughout his career, drawn as he was to his heritage and his home, Moses worked diligently, in two societies American and British-American to advance the interests of New Brunswick and the rest of British America.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.308
Threshold uncertainty score0.620

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.004
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.001

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 head0.007
GPT teacher head0.179
Teacher spread0.172 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Northern Mariner / Le marin du nordSame topicCanadian Identity and HistoryFrench-language works237,207