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Record W2242477359

Organic milk: what are the costs?

2000· article· en· W2242477359 on OpenAlexaboutno aff
M. Morisset, David N. Gilbert

Bibliographic record

VenueBulletin. International Dairy Federation · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsPanacea (medicine)Production (economics)Organic farmingOrder (exchange)AgricultureBusinessGovernment (linguistics)Organic productAgricultural scienceEconomicsAgricultural economicsMicroeconomicsFinanceEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

Drawing on Canadian and Danish data, this text deals with the question of costs and income for dairy producers interested in making the transition toward organic farming practices. These data allow for the comparison of yields, expenses and income of organic farmers with those of conventional farmers. However, before analysing the results, some qualifications are in order. (1) Inasmuch as the environmental costs of these practices have not been taken into account, full comparisons cannot be made. (2) Research in organic production has not reached the level of development as has that of its conventional counterpart. (3) Transition costs must also be considered when comparing the situations. (4) While costs may have an impact on interest in organic milk production, income can be equally important. (5) Comparisons paint a static picture of the situation as potential variation in input costs cannot be taken into account. It can be concluded from the analysis that, while not a universal panacea, organic milk production appears to be a serious option in terms of agricultural practices. It has so far allowed a still limited number of farm operations over a relatively short period of time to obtain results that are just as satisfactory as those from conventional farming. A healthy initial financial situation and good management skills on the part of farmers as well as government support and the market's willingness to pay are certainly factors which will facilitate the transition. When the medium and long-term environmental gains are also counted in, it is likely that farmers, the authorities and the population will find this option all the more appealing.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0250.002

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 head0.011
GPT teacher head0.200
Teacher spread0.189 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2000
Admission routes1
Has abstractyes

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