2000 Front Materials- Quarter 1
Bibliographic record
Abstract
What agricultural and resource economists are finding about food, farm, and resource issues• FLEMING says that swine producers in Kenrucky must adhere ro "setbacks" in the fields where they dispose of manure.The lengm of the setback varies depending on whether the operaror incorporates the manure inro the soi l or spreads it on the surface.The setback distance for surface disposal must exceed me setback for incorporation by at least 1,485 feet before incorporation becomes me least-cost method of disposal.(Fleming, Ronald A. "The Economic Impact of Setback Requirements ... " Land Economics, 75(November 1999):579-591.)• THOMPSON says that one problem associated with research on animal cloning is that it takes val uab le medical research resources away from on human-rel ated biomedical problems.(Thompson, Paul."Ethical Issues in Livesrock Cloning."Jou rnaL of AgricuLturaL andEnvironmentaLEthics, 11 (no.3, 2000): 197-21 7.) • HONG AND ADAMS say that households recycle some of their waste only ro avoid increases in contractual waste collection fees .(I'll recycle only when my garbage can gets full.)(Hong, Seonghoon and Richard Adams, "Ho usehold Responses ro Price Incenrives for Recycling ... " Land Economics, 75(November 1999):505-514.)• VAN DALEN says that Nobel laureates in eco nomics made their most creative conrriburions between the ages of29 and 38.Moreover, most of their fundamenral work was done by them writing alone.(Van Dalen, Hendrik P "The Golden Age of Nobel Laureates." The American Economist, 43(Fal I1 999):17-35.)• HATCHER, JAFFRY, THEBAUD, AND BENNETT found evidence that fishermen who thought they were directly involved in the regularory process were more likely ro comply with quota restriccions than those who were outside the regularory loop.These same fishers thought that most of their peers felt mat exceeding quotas was wrong but it was an economic necessity.(Hatcher, Aaron, Shabbar Jeffry, Olivier Thebaud, and Elizabeth Bennett."Social Influences Affecting Compliance with Fishery Regulations." (Forthcoming, Land Economics, 76(August 2000.)• KALOF, DIETZ, STERN, AND GUAGNANO found that in a limited sample, 5.2 percenr of American adults considered themselves vegeta rians.Most preferred mis dietary choice because of co ncern for the environment rather than because of a dietary reason or because of feelings abo ut animal rights.(Kalof, Linda, T. Dietz, Pc.Stern, and G.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.849 | 0.714 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".