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Record W3124366263 · doi:10.1080/01615440.2020.1853643

The Capacity Trend Method: A new approach for enumerating the Newfoundland cod fisheries (1675–1790)

2021· article· en· W3124366263 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHistorical Methods A Journal of Quantitative and Interdisciplinary History · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
FundersEuropean Research Council
KeywordsRobustness (evolution)FisheryPeriod (music)New englandMissing dataValue (mathematics)Operations researchComputer scienceGeographyEngineeringLawBiologyMachine learningPolitical science

Abstract

fetched live from OpenAlex

We apply a novel methodology to the study of the Newfoundland cod fisheries in order to determine a reasoned and acceptable chronological value series for total catch amounts in the early modern period where data are scarce. The paper focuses on the two main protagonists in the Newfoundland fisheries arena in that period: France and England. The period 1675–1790 has been selected as a viable and representative chronology for a case study where data, while available in part, are limited and often missing. The new methodology proposed here enables further exploration, input and assessment such that an ever-greater level of accuracy, integrity and robustness may be achieved in future.

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.

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)0.003
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.590
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.209
GPT teacher head0.368
Teacher spread0.159 · 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