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Record W7009877877

2013 Fiske Guide Cites Lawrence’s University’s “Eclectic Approach to Learning”

2012· article· en· W7009877877 on OpenAlexaboutno aff

Bibliographic record

VenueLux Scholarship And Creativity At Lawrence University (Lawrence University) · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
Fundersnot available
KeywordsCITESAppealListing (finance)Higher educationResource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

“A school that can appeal to both the left and right side of students’ brains.” That’s how former New York Times education editor Edward Fiske describes Lawrence University in his just-published “Fiske Guide to Colleges 2013.” The guide, a selective and systematic look at 319 colleges and universities in the United States, Canada and Great Britain, is published annually as a resource for college-bound students and their families on which to base their educational choices. In a profile of Lawrence, Fiske cites the college for its “eclectic approach to learning that attracts interested and interesting students from around the world.” The guide also highlights Lawrence’s commitment to individualized learning, the expertise of the faculty and its broad, off-campus study opportunities. Among the guides features: • Updated overviews of the best and most interesting colleges and universities with details on academics, campus setting, student body, financial aid, housing, food, social life and extracurricular activities • A listing of schools that no longer require the SAT or ACT of all applicants, of which Lawrence is one. • An “If You Apply To” feature, which contains vital information about each college’s admission policies, including deadlines and essay topics. Fiske spent 17 years as education editor of the New York Times. He compiles his guide as a tool to broaden students’ horizons about American higher education and help them select the right college that coincides with their particular needs, goals, interests, talents and personalities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0050.001
Scholarly communication0.0000.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.261
Teacher spread0.224 · 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
Published2012
Admission routes1
Has abstractyes

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