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Record W1983338783 · doi:10.1080/03632415.2012.696025

Leslie Edward Whitesel

2012· article· en· W1983338783 on OpenAlexaboutno aff
Bernard Einar Skud

Bibliographic record

VenueFisheries · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerFisheryNavyService (business)Fish <Actinopterygii>ManagementCommissionWildlifeFishingPolitical scienceBusinessLawEcology

Abstract

fetched live from OpenAlex

Ed was also fortunate to meet and marry Margaret MacLeod of Vancouver, British Columbia, in 1941. Considering that Marge's father was a federal fisheries officer, Ed was lucky to pass muster. He also passed muster when he served as an officer in the U.S. Navy in the South Pacific from 1944 to 1946. After his military service, he returned to the Salmon Commission and continued his salmon research—the highlight of which was the publication he coauthored with Robert Clutter, “Collection and Interpretation of Sockeye Salmon Scales” (IPSFC Bulletin IX). In 1955 he accepted a position in Juneau, Alaska, as a supervisory fishery management biologist with the Bureau of Sport Fisheries, U.S. Fish and Wildlife Service. After Alaska gained statehood in 1959, there was a transitional period during which federal agencies were to divest their territorial responsibilities, and Ed saw to those concerning sport fisheries. In 1961 he transferred to the regional office of the Fish and Wildlife Service in Portland, Oregon, and was involved with federal aid. He administered the Dingell/Johnson Grant and Aide Program in seven states of the Pacific Region. In 1965 Ed became the federal aid coordinator in the Midwest region of the Bureau of Commercial Fisheries in Ann Arbor, Michigan, where—along with other duties—he administered the Commercial Fisheries and Development Act (PL88-309). Under the Reorganization Plan of 1970, when Bureau of Commercial Fisheries became the National Marine Fisheries Service, the Ann Arbor staff was relocated to the northeast region in Glouscester, Massachusetts, where the federal aid program serviced 19 states from Maine to Virginia, as well as to the Great Lakes states. In 1972, Ed got back to his first love—salmon. He rejoined the U.S. Bureau of Sport Fisheries in Stockton, California, and was the service's representative on the four-agency study of the Sacramento–San Joaquin Estuary. The other participating agencies were the Bureau of Reclamation and the California Departments of Fish and Game and Water Resources. Ed designed a trawl that skimmed the surface in order to sample migrations of young salmon. He gave testimony at public hearings and counseled scientists working on the program. His role and contributions in the joint study—as well as his career-long professionalism and dedication—were recognized by the regional office when he retired in 1977 by the naming of a 40-foot research vessel after him—the Leslie Edward Whitesel. A Canadian coworker from the 1940s remembered Ed: “He always was a favorite with field crews, as he would dig right in, no matter what you were doing, and offer his perspective on how these projects contributed to the aim of the Commission. To my mind he was a fine ambassador for IPSFC.” Indeed, remarks about Ed's work ethics were echoed by others from among his countrywide contacts, and his role as an ambassador applied to all of the agencies he represented during his 40-year career. His goodwill attitude was also evident in his contributions and participation in the community and in his church. Ed is survived by his two daughters, Sally (Leo) Miedler of Maumee, Ohio, and Leslie (John) Peck of Maple City, Michigan; five grandchildren; and eight great-grandchildren. A memorial service to celebrate Ed's life was held March 24, at the Northern Lakes Community Church in Traverse City.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0120.003

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 head0.013
GPT teacher head0.202
Teacher spread0.190 · 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 designObservational
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
Published2012
Admission routes1
Has abstractyes

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