Lawrence University Cited in 2014 “Fiske Guide to Colleges”
Bibliographic record
Abstract
Citing its “outstanding liberal arts curriculum, knowledgeable and caring faculty and an administration that treats students like adults,” former New York Times education editor Edward Fiske included Lawrence University in his 30th edition of the just-published “Fiske Guide to Colleges 2014 (Watermarked PDF).” The guide, a selective and systematic look at more than 300 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. Institutions selected for inclusion are profiled on a broad range of subjects, including student body, academics, social life, financial aid, campus setting, housing, food, and extracurricular activities. 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 features included in the guide are: Overlap school suggestions based on which colleges share the most common applications a listing of schools that no longer require the SAT or ACT of all applicants, of which Lawrence is one. a preprofessional guide that outlines the best schools based on majors or course of study a Sizing-Yourself-Up questionnaire that will help you figure out what kind of school is best for you Fiske, who spent 17 years at education editor of the New York Times, 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.097 | 0.081 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".