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Record W78610784

Interview of Marc A. Moreau, Ph.D.

2008· article· en· W78610784 on OpenAlexaboutno aff
Marc A. Moreau, Elizabeth Wagner

Bibliographic record

VenueLa Salle University Digital Commons (La Salle University) · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsnot available
Fundersnot available
KeywordsArt
DOInot available

Abstract

fetched live from OpenAlex

Marc Moreau was born in 1948 in Lewiston, Maine. His family is French Canadian, and the part of town where he grew up was a pocket for French-speaking people. It was referred to as a "Petit-Canada." Lewiston's economy centered on textile mills. All of his grandparents and both of his parents worked in the mills during their lives. His mother later became a nurse during World War II, and his father served in the army during that time but later returned to the mills. Moreau has a younger sister and brother. He delivered French newspapers as a boy and attended a grade school run by Dominican nuns. He attended Brothers of the Sacred Heart High School. He became an avid trumpet player at a young age and received a full scholarship to study music at the University of Connecticut. However, he realized that his musical skills did not match those of the other students, so he began to look for a different interest. He found one in philosophy, and proceeded on to Temple's doctoral program for philosophy. While at Temple he fought the draft for Vietnam and met his first wife. They divorced after six years and he met and married his current wife, Juliet. Juliet has two children from her first marriage, but he considers her children's children his grandchildren. At the time of the interview, he was chair of the philosophy department at La Salle University.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.188
Teacher spread0.142 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2008
Admission routes1
Has abstractyes

Explore more

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