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Record W2318569107 · doi:10.1086/ahr.116.4.1123

Matthew McKenzie . Clearing the Coastline: The Nineteenth‐Century Ecological and Cultural Transformation of Cape Cod . Hanover, N.H.: University Press of New England. 2010. Pp. xv, 227. Cloth $85.00, paper $35.00.

2011· article· en· W2318569107 on OpenAlexaff
Miriam Wright

Bibliographic record

VenueThe American Historical Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicColonialism, slavery, and trade
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCapeFishingFish <Actinopterygii>Natural (archaeology)White (mutation)HistoryGeographyFisheryArchaeology

Abstract

fetched live from OpenAlex

One of the central questions of Matthew McKenzie's engaging book is how Cape Cod, Massachusetts, became more closely associated with images of “pristine coastlines” and resorts for America's wealthy than with fish nets. For thousands of years, aquatic life had sustained its human inhabitants, from the native Wampanoag to the English who began moving to the Cape in the 1600s. By the end of the nineteenth century, however, the commercial fishing economy that had dominated the region for several hundred years had collapsed. Fishing families were leaving or finding other ways to make a living. At the same time, Cape Cod began attracting artists and writers who celebrated its natural features but ignored the area's maritime and fishing past. To explain this change, McKenzie explores the dynamics of the relationships among humans, aquatic life, and the marine and river environments from the early seventeenth century to the end of the nineteenth. Building upon approaches developed by Arthur McEvoy, Richard White, and others, McKenzie argues that to understand what happened in Cape Cod, we need to examine the intertwining of “labor, environment, science, culture and ecology” (p. 178).

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)0.002
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.353
Threshold uncertainty score0.702

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.003

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 head0.046
GPT teacher head0.269
Teacher spread0.223 · 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
GenreReview

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
Published2011
Admission routes1
Has abstractyes

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