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description Publicationkeyboard_double_arrow_right Article 2020Resilience Alliance, Inc. SSHRC, NSF | FW-HTF-P: Anticipating Ri...SSHRC ,NSF| FW-HTF-P: Anticipating Risks and Benefits of Precision Agriculture (PA) or the Future of Agricultural Work and Workforce: A Multi-Stakeholder Research AgendaCourtney R. Hammond Wagner; Suzie Greenhalgh; Meredith T. Niles; Asim Zia; William B. Bowden;Water quality policy for agricultural lands seeks to improve water quality by changing farmer behavior. We investigate farmer behavior in three water quality regimes that differ by rule structure to examine the fit and interplay of each policy within its social-ecological context, important aspects for improving water quality. Vermont, USA's practice-based policy requires the adoption of specific practices, whereas New Zealand's Lake Taupo and Lake Rotorua performance-based policies require farmers to meet a numeric limit for nutrient loss on their farm. Across the three regions we interviewed 38 farmers to elicit mental models of nutrient management changes. We utilized the social-ecological systems (SES) framework to guide mental model elicitation, drawing on farmers' perceptions of the SES to identify salient aspects for behavior. Mental models were grouped by region and analyzed using network analysis. Farmers in all regions self-report high levels of behavior change and cite the policies as key drivers of behavior. This suggests that each policy fits in that it is achieving desired behavior change. However, different behavioral patterns emerged across the regions that we hypothesize have implications for biophysical fit: structural changes dominate in Vermont (e.g., buffers) and system changes in Taupo (e.g., switch from dairy support to beef cattle). The interplay of the policy in each setting, such as with incentive programs in Vermont and a market for nitrogen in Taupo, contributed to the different behavioral patterns. Additionally, access to capital in some form is required for farmers to achieve changes associated with higher biophysical fit. The social fit of the policies also varied, evidenced by dramatic upheaval in Taupo to mostly neutral perceptions of the policy in Vermont. We conclude that regions considering a shift to water quality rules for farms should carefully consider behavioral dynamics in policy design to achieve water quality goals.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5751/es-12034-250435&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5751/es-12034-250435&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint , Other literature type 2014 Italy, United States, Belgium, SwitzerlandProceedings of the National Academy of Sciences NSF | CDI-Type II: Collaborativ..., SSHRCNSF| CDI-Type II: Collaborative Research: Dynamical processes in interdependent techno-social networks ,SSHRCAlexander M. Petersen; Santo Fortunato; Raj Kumar Pan; Kimmo Kaski; Orion Penner; Armando Rungi; Massimo Riccaboni; H. Eugene Stanley; Fabio Pammolli;Reputation is an important social construct in science, which enables informed quality assessments of both publications and careers of scientists in the absence of complete systemic information. However, the relation between reputation and career growth of an individual remains poorly understood, despite recent proliferation of quantitative research evaluation methods. Here we develop an original framework for measuring how a publication's citation rate $\Delta c$ depends on the reputation of its central author $i$, in addition to its net citation count $c$. To estimate the strength of the reputation effect, we perform a longitudinal analysis on the careers of 450 highly-cited scientists, using the total citations $C_{i}$ of each scientist as his/her reputation measure. We find a citation crossover $c_{\times}$ which distinguishes the strength of the reputation effect. For publications with $c < c_{\times}$, the author's reputation is found to dominate the annual citation rate. Hence, a new publication may gain a significant early advantage corresponding to roughly a 66% increase in the citation rate for each tenfold increase in $C_{i}$. However, the reputation effect becomes negligible for highly cited publications meaning that for $c\geq c_{\times}$ the citation rate measures scientific impact more transparently. In addition we have developed a stochastic reputation model, which is found to reproduce numerous statistical observations for real careers, thus providing insight into the microscopic mechanisms underlying cumulative advantage in science. Comment: Final published version of the main manuscript including additional analysis: 9 pages, 4 figures, 1 table, and full reference list, including those in the Supplementary Information. For the SI Appendix, see http://physics.bu.edu/~amp17/webpage_files/MyPapers/Reputation_SI.pdf
RE.PUBLIC@POLIMI Res... arrow_drop_down eScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaeScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaInfoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2013License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.1323111111&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu204 citations 204 popularity Top 1% influence Top 1% impulse Top 1% Powered by BIP!more_vert RE.PUBLIC@POLIMI Res... arrow_drop_down eScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaeScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaInfoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2013License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.1323111111&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article 2020Resilience Alliance, Inc. SSHRC, NSF | FW-HTF-P: Anticipating Ri...SSHRC ,NSF| FW-HTF-P: Anticipating Risks and Benefits of Precision Agriculture (PA) or the Future of Agricultural Work and Workforce: A Multi-Stakeholder Research AgendaCourtney R. Hammond Wagner; Suzie Greenhalgh; Meredith T. Niles; Asim Zia; William B. Bowden;Water quality policy for agricultural lands seeks to improve water quality by changing farmer behavior. We investigate farmer behavior in three water quality regimes that differ by rule structure to examine the fit and interplay of each policy within its social-ecological context, important aspects for improving water quality. Vermont, USA's practice-based policy requires the adoption of specific practices, whereas New Zealand's Lake Taupo and Lake Rotorua performance-based policies require farmers to meet a numeric limit for nutrient loss on their farm. Across the three regions we interviewed 38 farmers to elicit mental models of nutrient management changes. We utilized the social-ecological systems (SES) framework to guide mental model elicitation, drawing on farmers' perceptions of the SES to identify salient aspects for behavior. Mental models were grouped by region and analyzed using network analysis. Farmers in all regions self-report high levels of behavior change and cite the policies as key drivers of behavior. This suggests that each policy fits in that it is achieving desired behavior change. However, different behavioral patterns emerged across the regions that we hypothesize have implications for biophysical fit: structural changes dominate in Vermont (e.g., buffers) and system changes in Taupo (e.g., switch from dairy support to beef cattle). The interplay of the policy in each setting, such as with incentive programs in Vermont and a market for nitrogen in Taupo, contributed to the different behavioral patterns. Additionally, access to capital in some form is required for farmers to achieve changes associated with higher biophysical fit. The social fit of the policies also varied, evidenced by dramatic upheaval in Taupo to mostly neutral perceptions of the policy in Vermont. We conclude that regions considering a shift to water quality rules for farms should carefully consider behavioral dynamics in policy design to achieve water quality goals.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5751/es-12034-250435&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu2 citations 2 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5751/es-12034-250435&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Preprint , Other literature type 2014 Italy, United States, Belgium, SwitzerlandProceedings of the National Academy of Sciences NSF | CDI-Type II: Collaborativ..., SSHRCNSF| CDI-Type II: Collaborative Research: Dynamical processes in interdependent techno-social networks ,SSHRCAlexander M. Petersen; Santo Fortunato; Raj Kumar Pan; Kimmo Kaski; Orion Penner; Armando Rungi; Massimo Riccaboni; H. Eugene Stanley; Fabio Pammolli;Reputation is an important social construct in science, which enables informed quality assessments of both publications and careers of scientists in the absence of complete systemic information. However, the relation between reputation and career growth of an individual remains poorly understood, despite recent proliferation of quantitative research evaluation methods. Here we develop an original framework for measuring how a publication's citation rate $\Delta c$ depends on the reputation of its central author $i$, in addition to its net citation count $c$. To estimate the strength of the reputation effect, we perform a longitudinal analysis on the careers of 450 highly-cited scientists, using the total citations $C_{i}$ of each scientist as his/her reputation measure. We find a citation crossover $c_{\times}$ which distinguishes the strength of the reputation effect. For publications with $c < c_{\times}$, the author's reputation is found to dominate the annual citation rate. Hence, a new publication may gain a significant early advantage corresponding to roughly a 66% increase in the citation rate for each tenfold increase in $C_{i}$. However, the reputation effect becomes negligible for highly cited publications meaning that for $c\geq c_{\times}$ the citation rate measures scientific impact more transparently. In addition we have developed a stochastic reputation model, which is found to reproduce numerous statistical observations for real careers, thus providing insight into the microscopic mechanisms underlying cumulative advantage in science. Comment: Final published version of the main manuscript including additional analysis: 9 pages, 4 figures, 1 table, and full reference list, including those in the Supplementary Information. For the SI Appendix, see http://physics.bu.edu/~amp17/webpage_files/MyPapers/Reputation_SI.pdf
RE.PUBLIC@POLIMI Res... arrow_drop_down eScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaeScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaInfoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2013License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.1323111111&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu204 citations 204 popularity Top 1% influence Top 1% impulse Top 1% Powered by BIP!more_vert RE.PUBLIC@POLIMI Res... arrow_drop_down eScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaeScholarship - University of CaliforniaArticle . 2014Data sources: eScholarship - University of CaliforniaInfoscience - EPFL scientific publicationsOther literature typeData sources: Infoscience - EPFL scientific publicationshttps://doi.org/10.48550/arxiv...Article . 2013License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1073/pnas.1323111111&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu