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Record W2295604433

Recreational Development and the Lake Erie Shore Photographs,1967

2010· article· en· W2295604433 on OpenAlexaboutno aff
Jen Goul

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsShoreRecreationNavyGeographyPeninsulaArchaeologyFoundation (evidence)HistoryLawOceanographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

John N. Jackson was born and raised in London England. He served in the Royal Navy, acquired a B.A. and a Ph.D, conducted research for a city planning office and lectured at the University of Manchester. He joined Brock University’s faculty in 1965 as a Professor of Applied Geography. Since his retirement in 1991 he has been Professor Emeritus to Brock. Throughout his time in academia Jackson has focused his research on the history of the modern city, both throughout Europe and Canada. Jackson has also completed specific research on the Niagara Peninsula; including industrial geography, recreation along the Lake Erie shore, St. Catharines early history, the Welland Canals, railway development, comparisons across the Niagara River. While living in the Niagara region Jackson has become involved in many community events. He has been the Director for the Bruce Trail Association, President of the Welland Canals Foundation, and been involved in local historical groups throughout the Niagara region.

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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.685
Threshold uncertainty score0.627

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0330.003

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 head0.005
GPT teacher head0.147
Teacher spread0.143 · 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
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

Citations0
Published2010
Admission routes1
Has abstractyes

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