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Record W4255478582 · doi:10.7202/1015917ar

Introduction

2007· article· en· W4255478582 on OpenAlexfundvenueaboutno aff
Steven High

Bibliographic record

VenueUrban History Review · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNipissing University
KeywordsTRACE (psycholinguistics)IdeologyMeaning (existential)FishingPoliticsGovernment (linguistics)Position (finance)HistoryPolitical scienceEnvironmental ethicsLawEconomicsEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Historian Rosemary Ommer gave the W. Stewart MacNutt Memorial Lecture at the University of New Brunswick in 1993, a year after the collapse of groundfish stocks had led the federal government to issue fishing moratoria in Atlantic Canada. It was entitled "One Hundred Years of Fishery Crises in Newfoundland." As a historian of the fishery and a resident of St. John’s, Ommer used this occasion to grapple with the meaning of the dire economic crisis now facing Newfoundlanders and to reflect on the historian’s role in the societal search for answers. What can the historian offer, she asked? A first step, Ommer told the audience, was for scholars to understand the crisis and provide insight into what went wrong: "We must trace where it came from, we must ask why it was not foreseen and prevented, and we must seek out the most useful approach to a solution for the future. In so doing, we will need to be aware of the implicit ideologies, beliefs and pressures that underlie the thinking of the policy makers of the day." A second step was to ensure that the "historical record" that was already being marshalled in support of one political position or another was not distorted beyond recognition. A steady stream of studies has since appeared on the crisis in the Atlantic fisheries.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.411
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.023
GPT teacher head0.247
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2007
Admission routes3
Has abstractyes

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