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Record W7029003271

A Guide to the Records of University President Stephen Feldman

2008· other· en· W7029003271 on OpenAlexaboutno aff

Bibliographic record

VenueNSUWorks (Nova Southeastern University) · 2008
Typeother
Languageen
FieldArts and Humanities
TopicLinguistic research and analysis
Canadian institutionsnot available
Fundersnot available
KeywordsMiamiEvent (particle physics)Nova (rocket)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

General Correspondence, clippings, memos, and agendas are present in the administrative records of Stephen Feldman, third president of Nova University (later known as Nova Southeastern University). The bulk of the material is from his inauguration on January 22, 1993 through his resignation on June 30, 1994. The correspondence deals with the daily activities of the University, especially with Board of Trustees and donors. Only a few letters are originals and the copies were originally bound quarterly in soft-cover binders. Clippings from local publications cover President Feldman’s arrival and departure from Nova as well as overviews on Nova University in general. There are two bound diaries that contain the daily appointments of the President. The most significant event documented in the collection is the merger of Nova University and Southeastern University of the Health Sciences which officially took place on January 1, 1994. Other events include the establishment of a recycling program, membership in the South Florida Education Center cooperative, and the opening of the Miami Dolphins Training Facility on the main campus. A significant amount of the collection concerns the planning and execution of Stephen Feldman's inauguration as President. A large binder contained the planning documents of different events associated to the inauguration; it was disassembled but dividers were kept. There is also a 3 ½ floppy disk with documents related to the inauguration.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.036
Threshold uncertainty score0.993

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.034
GPT teacher head0.232
Teacher spread0.197 · 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
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
Published2008
Admission routes1
Has abstractyes

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