Underdetermination and evidence-based policy.

Safety assessment of technologies and interventions is often underdetermined by evidence. For example, scientists have collected evidence concerning genetically modified plants for decades. This evidence was used to ground opposing safety protocols for "stacked genetically modified" plants, in which two or more genetically modified plants are combined. Evidence based policy would thus be rendered more effective by an approach that accounts for underdetermination. Douglas (2012) proposes an explanatory approach, based on the criteria of transparency, empirical competence, internal consistency of explanations, and predictive potency. However, sometimes multiple explanations can satisfy these criteria. We propose an additional criterion based on converse abduction, where explanations are selected on the basis of ontological background assumptions as well as by evidence. We then apply our proposed scheme to the case of the regulation of stacked genetically modified plants. We discuss the implications and suggest follow-up work concerning the generalizability of the approach.

Philosophical bias is the one bias that science cannot avoid.

Scientists seek to eliminate all forms of bias from their research. However, all scientists also make assumptions of a non-empirical nature about topics such as causality, determinism and reductionism when conducting research. Here, we argue that since these 'philosophical biases' cannot be avoided, they need to be debated critically by scientists and philosophers of science.

How biological background assumptions influence scientific risk evaluation of stacked genetically modified plants: an analysis of research hypotheses and argumentations.

Scientific risk evaluations are constructed by specific evidence, value judgements and biological background assumptions. The latter are the framework-setting suppositions we apply in order to understand some new phenomenon. That background assumptions co-determine choice of methodology, data interpretation, and choice of relevant evidence is an uncontroversial claim in modern basic science. Furthermore, it is commonly accepted that, unless explicated, disagreements in background assumptions can lead to misunderstanding as well as miscommunication. Here, we extend the discussion on background assumptions from basic science to the debate over genetically modified (GM) plants risk assessment. In this realm, while the different political, social and economic values are often mentioned, the identity and role of background assumptions at play are rarely examined. We use an example from the debate over risk assessment of stacked genetically modified plants (GM stacks), obtained by applying conventional breeding techniques to GM plants. There are two main regulatory practices of GM stacks: (i) regulate as conventional hybrids and (ii) regulate as new GM plants. We analyzed eight papers representative of these positions and found that, in all cases, additional premises are needed to reach the stated conclusions. We suggest that these premises play the role of biological background assumptions and argue that the most effective way toward a unified framework for risk analysis and regulation of GM stacks is by explicating and examining the biological background assumptions of each position. Once explicated, it is possible to either evaluate which background assumptions best reflect contemporary biological knowledge, or to apply Douglas' 'inductive risk' argument.

Associations between the time of conception and the shape of the lactation curve in early lactation in Norwegian dairy cattle.

BACKGROUND: This study was carried out to determine if an association exists between the shape of the lactation curve before it is influenced by the event of conception and the time from calving to conception in Norwegian dairy cattle. Lactation curves of Norwegian Red cows during 5 to 42 days in milk (DIM) were compared between cows conceiving between 43 and 93 DIM and cows conceiving after 93 DIM. METHODS: Data from 23,049 cows, represented by one lactation each, with 219,538 monthly test days were extracted from the Norwegian Dairy Herd Recording System, which represents 97% of all Norwegian dairy cows. Besides veterinary treatments, these records also included information on daily milk yield at monthly test days. The data were stratified by parity groups (1, 2, and 3 and higher) and time to conception periods (43-93 DIM and >93 DIM). The sample was selected using the following selection criteria: conception later than 42 DIM, calving season July to September, no records of veterinary treatment and the level of energy fed as concentrates between 8.69 and 12.83 MJ. The shape of the lactation curves were parameterized using a modified Wilmink-model in a mixed model analysis. Differences in the parameters of the lactation curves with different conception times were evaluated using confidence intervals. RESULTS: Lactation curves characterized by a low intercept and a steep ascending slope and a steep descending slope were associated with early conception across all parities. The peak milk yield was not associated with time of conception. CONCLUSIONS: A practical application of the study results is the use of the shape of the lactation curve in future herd management. Groups of cows with impaired reproductive performance may be identified due to an unfavorable shape of the lactation curve. Monitoring lactation curves and adjusting the feeding strategy to adjust yield therefore may be useful for the improvement of reproductive performance at herd level.

Mastitis and the shape of the lactation curve in Norwegian dairy cows.

An investigation of the shape of the lactation curve and the mastitis incidence was conducted to identify whether management interventions of the lactation curve constitute a potential for reducing incidence of mastitis at herd level. Lactation curves were estimated to describe the variation of daily milk yield during the 305-d lactation period in Norwegian Red cows. Associations between mastitis incidence at herd level and lactation curve characteristics such as production level at onset of lactation, magnitude and time of peak milk yield, and increase and decrease of milk yield rates were studied. Data from 250,303 lactations occurring during 2005 and 2006 from 14,766 herds were obtained from the Norwegian Dairy Herd Recording System. Besides veterinary treatments, the records included information on monthly test-day milk yields. The shapes of the lactation curves at herd level were parameterized using a modified Wilmink model in two separate mixed model analyses. In the first analysis a subset of lactations with no records of veterinary treatments was used. Lactation curves from herds with high (>0·31 cases/305-d lactation) and low (<0·07 cases/305-d lactation) herd mastitis incidence rate were parameterized and compared for three separate strata of parity. The result showed that high herd mastitis incidence rate was associated with a low intercept (P<0·05), a steep slope before peak milk yield (P<0·01) and a rapid decline after peak milk yield (P<0·01). In the second analysis a subset of high-yielding lactations with veterinary treatments of mastitis only and lactations with no records of veterinary treatment were compared. This was done to investigate whether the findings at herd level were also reflected at cow level. These results showed that lactation curves from lactations with mastitis cases were associated with a steep slope before peak milk yield (P<0·05) in second and later parities and a rapid decline after peak milk yield (P<0·01) in all three parity groups.