Discussion and Conclusions challenges and impact on working conditions and employment – COVID update / Moderated by Diesis Network and FGB 12. 10 – 12.30
Discussion and Conclusions. Present-day Dutch krijgen is a verb with a rich past. In this chapter I have given a detailed overview of how it has developed from its Middle Dutch use to the present. In the 14th century, krijgen is used in intransitive, transitive and complement constructions. These uses are all highly agentive, although the transitive use of krijgen already shows different degrees of agentivity. In the 15th century, the intransitive use has become almost completely extinct. The transitive shows a sharp decrease in agentive use, a process that will continue until at least the 17th century. This change occurs similarly with an increase in the use of objects that denote subject states. The decrease in agentivity of krijgen seems to take off in this particular use, followed by abstract objects a century later. The use with concrete objects does not seem to lose its agentivity until the 17th century.
Discussion and Conclusions. This paper develops a novel theoretical approach to study how interest groups’ member involvement and organizational capacity affect their degree of access to EU public officials. In this way, the findings inform us about the potential democratic contribution of groups 93 with access to Commission officials – who are expected to reach out to groups that can increase the legitimacy and efficiency of the policy process. Before discussing the main findings, this last section will reflect on three aspects related to the research design. First, this paper has analyzed how interest groups’ organizational structure affects access by using reported survey data that tap key organizational elements. Thus, the paper looks at the formal opportunities for the participation of members, and not at the actual involvement of members. In addition to examining actual involvement of members, future research could examine whether the organizational structures related to member involvement lead to an accurate alignment of the preferences of members and the positions of group leaders (Xxxxxx, 2016, 2018). Second, the groups included in the sample are active at the EU level and gained ac- cess to Commission officials. The need for professionalized and technical expertise might be accentuated in the Commission, which as the bureaucratic institution in charge of developing policy proposals is mostly concerned about the technicalities that would make a proposal viable. We may find different results if we study more politicized venues, such as the legislative arena where there is a higher demand for political knowledge (Grömping & Xxxxxx, 2019). In addition, the effects of these organizational dimensions and the ability to function as a transmission belt might work differently at the national level (cf., Berkhout et al., 2017). In that regard, members might have few selective incentives to get involved in the groups due to its EU focus which could ultimately affect the organizational attributes to involve members and have organizational capacity. Future research needs to assess the occurrence and validity of the main explanatory factors and their effects on the degree of access in (sub)national polities. Lastly, the paper focuses on the transmission belt function of membership-based interest groups. That is, it excludes non-membership organizations which according to the Trans- parency Register, represent almost half of the interest groups with access to Commission officials. The mai...
Discussion and Conclusions. Grant project objectives were met. One new high school unit, Chemistry, Fertilizer, and the Environment was developed for use in 8th – 12th grade classrooms. This unit is comprised of five lessons. These lessons teach students about: solutes and solvents, serial dilution and parts per million, plant nutrient requirements, best management practices for nutrient management, the nitrogen cycle, basic chemistry concepts, soil pH and nutrient availability, and testing soil samples for available nitrogen. Twelve lessons from the existing unit, What Do Plants Need to Grow? were updated for use in 2nd -4th grade classrooms. The lessons in this unit teach students about: basic plant parts and their functions, requirements for healthy plant growth, soil composition, and the role of decomposers. Students will conduct several investigations to observe plant root growth, phototropism, and the effects of different concentrations of fertilizer solutions on classroom plants. These units are aligned to the most recent Content Standards for California public schools. Lessons are designed to engage students through hands-on activities that allow them to explore the types of activities carried out by farmers and plant scientists to produce our food and fiber while practicing environmental stewardship. After participating in the lessons, students will have a better understanding of what plant nutrients are, why they are important, and how farmers and scientists are continually improving methods to provide crops with the right plant nutrients in the right amounts, at the right time and in the right place. The lessons from each unit were pilot tested in classrooms, reviewed by experts in the plant nutrient field, and presented to teachers at workshops. Workshop participants gave overall positive reviews of the lessons as seen in the “Results” section of the report. “Grab ‘n’ Go” teacher training kits were used in CFAITC workshops to train teachers how to use the lessons in their classrooms and are available for teachers to borrow if they lack the proper equipment to teach lab activities. At the time of this report, the units had only been available to teachers over the three months of the summer. Once school has been back in session for several months, CFAITC will gather data on how teachers used the lessons and what students gained from them. This data will be collected as part of CFAITC’s annual survey sent to thousands of teachers in CFAITC’s database each December.
Discussion and Conclusions. On its largest scales, the cosmic web of the Universe is not formed by isolated objects, but by continuously owing matter distributed in sheets, laments, and nodes. For
Discussion and Conclusions. The Copernicus Services and Space component requirements for in situ data in the Arctic Region have been collected and analysed. The analysis shows that although the monitoring of the Arctic in the future will rely heavily on satellite observations, it is mandatory for Copernicus to have timely access to a broad suite of in situ observation of sufficient quality and resolution in time and space. The Copernicus community has articulated clearly which variables are essential for their production line as well as their requirement for timely delivery and quality, while the resolution in time and space is still open for further clarification. The latter issue is being addressed in the Copernicus In Situ Coordination Information System (CIS2), established within the Copernicus In Situ Component led by EEA. The project group has collected a thorough, although not complete, overview of existing in situ data from the Arctic: • Data already used by the Copernicus Services and Space component • Data freely available at various national and international data repositories but still not used in the Copernicus production line • Data with restricted availability due to institutional and/or national data policies • Data collected in research projects without a data management structure enabling a free data exchange. A full overview of this data category may require further work A gap analysis has been performed by comparing the amount of existing data to the requirements for in situ data. The analysis is general in nature since a detailed gap analysis will require clear definitions of the required resolution in time and space. The analysis has identified two groups of data gaps:
1. Observations needed but do not exist. This kind of gap can be roughly identified by comparing the requirements and spatiotemporal distribution of the observations.
2. Observations exist but are not being used because
a. Data are not freely available due to for example. data policy, lack of institutional data management structure, research publication, economic benefit, technological confidentiality and even political issues.
b. They do not fit Copernicus purposes due to
i. Untimely availability - most of the applications have strong time limits, e.g. near real time forecast and validation need observations in near real time; interim reanalysis needs observations in interim scale, i.e., 1-12 months before production time.
ii. lack of sufficient metadata
iii. Inadequate quality - observations for...
Discussion and Conclusions. We have reviewed, applied and compared different methods for uncertainty-statistics in comparative LCA. We showed how deterministic LCA can lead to oversimplified results that lack information on significance and likelihood, and that these results do not constitute a robust basis for decision-making. In addition, we found that, while in most instances (seven out of ten impacts), the five methods concur with each other, we identified instances where the methods produce conflicting results. Discrepancies are due to differences in the setup of the analysis (i.e. overall or per run) which accounts or not for common uncertainties and due to accounting or not for the magnitude of the differences in performances. We identify two groups of methods according to the type of analysis they entail: exploratory and confirmatory methods. This division corresponds with the statistical theories by Xxxxx (1973), in which data analysis initially requires an exploratory phase without probability theory, so without determining significance levels or confidence intervals, followed by a confirmatory phase determining the level of significance of the appearances identified in the exploratory phase. Exploratory statistics help delve into the results from uncertainty analysis and confirmatory methods evaluate hypotheses and identify environmental differences deemed statistically significant. The NHST and modified NHST methods belong to the confirmatory group. Confirmatory methods are calculated per MC run, account for common uncertainties between alternatives and provide an absolute measure of statistical significance of the difference (Heijungs et al. 2017). These methods are appropriate for both single impact and multiple impact assessments and support statistical significance confirmation. NHST was shown to detect irrelevant differences of the means and to label them nevertheless as significant, while alternatives are considered to be indiscernible by modified NHST whenever the difference is small. The modified NHST approach is therefore recommended for confirmatory purposes and for all propagated LCA results, where the sample size in theory is indefinite and in practice is very large.
Discussion and Conclusions. 10.1. Constraints on sugarbeet production in the Imperial Valley. The economic requirements of the sugarbeet industry in the Imperial Valley constrain options for reduced pest management interventions. Avoidance of peak insect activity periods in fall by planting later in October is only available for a portion of the total crop. A sugarbeet factory is a significant capital asset. For it to be viable financially, it must operate for the longest period possible in any given location. Climate limits farming seasonally and correspondingly curtails the operation of sugar factories all over the world. A number of ingenious methods have been developed to extend the processing season for beet refineries. In the Imperial Valley, beet harvest starts in early April and lasts until mid-July, and sometimes until early August. Mid- summer harvests are unfavorable due to increasing rates of loss to root rots during extreme summer temperatures. This limits the harvest campaign to 3.5 to 4 months per year. As the harvest season progresses, yields increase until about the end of June, and then remain static or decline with respect to yield and sugar content in beets due to high levels of respiration during hot weather (Xxxxxx and Xxxxx, 2015). End of season crops become increasingly uneconomic due to rising costs for water, labor and pest management, and losses in root quality and to root rots. The April starting date for first harvests is a compromise between the financial needs of growers and the needs of the factory. The growers need a factory to process and market their crop, and the factory needs willing growers to produce the crop. April harvests are often uneconomic for growers due to lower yields. The need for early April harvest, however, requires that some beets be planted starting in early to the middle of September when temperatures and insect activity remain high, an unfavorable time from an IPM perspective, to support early April harvests. Later planted beets, (mid-October onwards) avoid some insect pressure at planting and establishment, but these crops tend to be harvested last the following summer when insect pressure is again increased and losses to wet rots start to occur. Water and pest management costs rise, while root quality (sugar %) declines, limiting
Discussion and Conclusions. 5 In this study we analyzed the distribution of ice concentrations estimated by analysts and forecasters visually using SAR imagery. Visually estimated ice concentrations were compared against three different standards: automatically calculated ice concentrations, automatically calculated ice concentrations that were validated by analysts, and the mode of visually estimated ice concentrations. In all three cases, visually estimated ice concentrations were over-estimated for low ice concentration categories (1/10 to 3/10) and had high variability for middle ice concentration categories (5/10, 6/10). In general, the ice con- 10 centrations estimates were consistent within analysts, and the analysts estimates were overall in agreement with the automated segmentation estimates (as shown by Figures 7 and 10, and the high values of the kappa statistics in Figure 13). The analysts’ ice concentration estimates compared to the automated segmentation estimates exhibit an over-estimation (for all ice concentration categories evaluated). This result was achieved not only when considering all polygons, but also when considering solely the polygons for which the automated segmentation was validated by the analysts (compare Figures 7 and
Discussion and Conclusions. 5.1 LCA The results of the LCA show that the implementation of the different SunHorizon technologies across the different demonstration sites result in significant environmental benefits, especially in terms of climate change, ozone layer depletion, consumption of fossil fuels and photochemical oxidation. In particular, TP2 and TP3 show significant environmental benefits for every impact category apart from Abiotic Depletion of resources. TP1 performs slightly worse in Acidification and Eutrophication, a trade-off resulting from the increase in electricity consumption, although it achieves meaningful reductions for climate change, consumption of fossil fuels, impact on the ozone layer and photochemical oxidation. For example, on average, reductions of 25.5% were achieved for TP1, 35.75% for TP2 and 62% for TP3 for the Global Warming category. This means that the large-scale deployment of SunHorizon technologies replacing conventional heating and cooling technologies would largely reduce the environmental footprint of the building stock, contributing to the objectives of carbon neutrality that the European Union has set for the next decades. However, these benefits are coupled to an increased consumption of resources, as a consequence of the construction and installation of the different components that are part of SunHorizon technologies. This is an important aspect that needs to be addressed to minimize the impact of the project, and suitable strategies to reduce the consumption of raw materials should be adopted, such as the use of secondary raw materials and service-life extension. It is important to say that this is a partial cradle-to-gate assessment with preliminary data for the operation of the demo sites. A more comprehensive analysis will be performed in the coming stages of the project as the monitoring stage progresses, providing more detailed information that will be presented in the updated version of this deliverable in M48.
