Academic literature on the topic 'Age of uncertainty'
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Journal articles on the topic "Age of uncertainty"
Buchan, James. "Age of uncertainty." Nursing Standard 31, no. 40 (May 31, 2017): 30. http://dx.doi.org/10.7748/ns.31.40.30.s26.
Full textGeoghegan, Peter. "The Age of Uncertainty." Political Insight 12, no. 1 (February 24, 2021): 3. http://dx.doi.org/10.1177/20419058211000993.
Full textMakriyannis, Christos, Robert J. Johnston, and Adam W. Whelchel. "Are Choice Experiment Treatments of Outcome Uncertainty Sufficient? An Application to Climate Risk Reductions." Agricultural and Resource Economics Review 47, no. 3 (April 10, 2018): 419–51. http://dx.doi.org/10.1017/age.2017.27.
Full textCOEN, DAVID, and ALASDAIR ROBERTS. "A New Age of Uncertainty." Governance 25, no. 1 (December 27, 2011): 5–9. http://dx.doi.org/10.1111/j.1468-0491.2011.01559.x.
Full textMelleuish, Gregory. "Understanding an “Age of Uncertainty”." Australian Journal of Politics & History 41, no. 1 (April 7, 2008): 130–34. http://dx.doi.org/10.1111/j.1467-8497.1995.tb01341.x.
Full textSharma, Bijay P., Seong-Hoon Cho, and Chad M. Hellwinckel. "Optimal Budget Allocations for Protected Area Acquisition To Store Carbon in a Local Community Under Economic Growth Uncertainty." Agricultural and Resource Economics Review 49, no. 2 (June 3, 2020): 209–36. http://dx.doi.org/10.1017/age.2020.10.
Full textAndo, Amy, Aparna Howlader, and Mindy Mallory. "Diversifying to Reduce Conservation Outcome Uncertainty in Multiple Environmental Objectives." Agricultural and Resource Economics Review 47, no. 2 (May 21, 2018): 220–38. http://dx.doi.org/10.1017/age.2018.7.
Full textMacEntee, Michael I., and Kavita R. Mathu-Muju. "Confronting dental uncertainty in old age." Gerodontology 31 (January 21, 2014): 37–43. http://dx.doi.org/10.1111/ger.12109.
Full textLi, Xueyan, and Chunxiao Zhang. "Delayed Age Replacement Policy with Uncertain Lifetime." Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/528726.
Full textNOVAK, J., C. JONES, and R. HALL. "Political advocacy in an age of uncertainty." Journal of Pediatric Health Care 16, no. 1 (January 2002): 44–45. http://dx.doi.org/10.1016/s0891-5245(02)40404-x.
Full textDissertations / Theses on the topic "Age of uncertainty"
Williams, Alexander. "Complexity & hegemony : technical politics in an age of uncertainty." Thesis, University of East London, 2015. http://roar.uel.ac.uk/4773/.
Full textMignault, David. "Cutting grass, the uncertainty of coming of age in the post-Fordist era." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ54515.pdf.
Full textHughes, Jennifer S. "Performance in a time of terror : Critical mimesis and the age of uncertainty." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.516436.
Full textLin, Zihan. "Context Informed Statistics in Two Cases: Age Standardization and Risk Minimization." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38327.
Full textKelly, Peter, and pkelly@deakin edu au. "Risk and the Regulation of Youth(ful) Identities in an Age of Manufactured Uncertainty." Deakin University. Bowater School of Management and Marketing, 1998. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20031212.114212.
Full textRosinski, Benjamin. "The role of entrepreneurship and uncertainty with reward-based crowdfunding in the digital age." Thesis, Uppsala universitet, Industriell teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355310.
Full textChilvers, Jason David. "Participatory environmental risk policy-making in an age of uncertainty : UK actor-networks, social learning and effective practice." Thesis, University College London (University of London), 2004. http://discovery.ucl.ac.uk/1446652/.
Full textPizarro, Muñoz Jenny Alejandra. "Efeitos de idade na sobrevivência aparente de aves de sub-bosque na floresta Amazônica." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/150592.
Full textThe observation of latitudinal gradients in bird life history traits has motivated the study of avian life history evolution and variability. A well-documented example is the variation in clutch size, where lower latitude birds tend to have smaller clutches than their higher latitude counterparts. A hypothesis that explains this variation proposes that survival in tropical latitudes is higher to compensate for smaller clutch size and prevent population extinctions. This explanation has had a wide acceptance and support by some studies, but has been questioned by others who have not found such higher survival rates in tropical birds. In an implicit manner, all these studies have based their results on adult survival. Populations with smaller clutch size would not be able to grow as well as populations with larger clutches; therefore one is justified to believe that something else must change with latitude. In the search for alternative explanations to the persistence of tropical bird populations with relatively small clutch sizes it has also been proposed that, if there were no differences in adult survival among latitudes, the fundamental trait that varies is juvenile survival, with higher survival rates for tropical juveniles birds than for temperate ones. However, currently there is little evidence that supports this conclusion. The contrasting results of those studies suggest a lack of a general consensus about the hypothesis that tropical birds have higher survival rates than birds of temperate regions, motivating the formulation of alternative hypotheses, and inviting further tests of the hypothesis. In our study we aim to a) assess the effect of age on survival in a tropical bird community, estimating age-specific annual apparent survival probabilities for a set of passerine understory birds from the central Brazilian Amazon; and b) contribute to the debate about the latitudinal gradient in adult survival by comparing our adult survival estimates to estimates of temperate-zone adult survival probabilities. To estimate the age-specific survival we fit to our data a hierarchical multispecies Cormack-Jolly-Seber (CJS) model for n species, that treats species-specific parameters as random effects that are estimated and that describe the whole assemblage of species; for comparison of methods, we also fit a fixed-effects version of the model. To age birds we use the cycle-based WRP system. We introduce a novel variant of CJS model with a mixture component for the survival of birds of uncertain age at the time of banding. We found strong effect of age on survival, with juveniles surviving less than adults; evidence of latitude effect on survival, that supports the widely accepted hypothesis of variation on survival with latitude; and methodological differences between random and fixed effects model related to precision of estimates and scope of inference, that lead us to conclude that random-effects models are more appropriate for our analysis. We conclude that there is no reason for an alternative latitudinal trend in juvenile survival to account for the general trend in clutch size.
Johansson, Jesper. "Success at the box office in the age of streaming services : An examination of how streaming services have impacted the dynamics of successful movies in the cinema." Thesis, Internationella Handelshögskolan, Jönköping University, IHH, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-50486.
Full textZaehle, Sönke. "Process-based simulation of the terrestrial biosphere : an evaluation of present-day and future terrestrial carbon balance estimates and their uncertainty." Phd thesis, Universität Potsdam, 2005. http://opus.kobv.de/ubp/volltexte/2005/526/.
Full textAt present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO2 concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies.
A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM.
This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO2 concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.
Kohlenstoffspeicherung in terrestrischen Ökosystemen reduziert derzeit die Wirkung anthropogener CO2-Emissionen auf das Klimasystem, indem sie die Wachstumsrate der atmosphärischer CO2-Konzentration verlangsamt. Die heutige terrestrische Kohlenstoffbilanz wird wesentlich von Klima- und Landnutzungsänderungen beeinflusst. Diese Einflussfaktoren werden sich auch in den kommenden Dekaden auf die terrestrische Biosphäre auswirken, und dabei möglicherweise zu einer positiven Rückkopplung zwischen Biosphäre und Klimasystem aufgrund von starken Bodenkohlenstoffverlusten in einem wärmeren Klima führen. Quantitative Abschätzungen der Wirkung dieser Einflussfaktoren - sowie der mit ihnen verbundenen Unsicherheit - auf die terrestrische Kohlenstoffbilanz sind daher sowohl für das Verständnis des Erdsystems, als auch für eine langfristig angelegte Klimaschutzpolitik relevant.
Um regionale Kohlenstoffbilanzen in die Zukunft zu projizieren, sind Modelle erforderlich, die die wesentlichen Prozesse des terrestrischen Kohlenstoffkreislaufes beschreiben. Die vorliegende Arbeit (1) analysiert die parameterbasierte Unsicherheit in Modellergebnissen eines der führenden globalen terrestrischen Ökosystemmodelle (LPJ-DGVM) im Vergleich mit unterschiedlichen ökosystemaren Messgrößen, sowie unter Klimawandelprojektionen, und erweitert damit bereits vorliegende Studien zu anderen Aspekten der Modelunsicherheit; (2) diskutiert unter theoretischen und experimentellen Aspekten verschiedene Hypothesen über die altersbedingte Abnahme des Waldwachstums, und implementiert die vielversprechenste Hypothese in das Model; (3) zeigt für eine europäische Fallstudie, wie Waldbestandsstatistiken erfolgreich für eine verbesserte Abschätzung von regionalen Kohlenstoffbilanzen in Wäldern durch prozessbasierten Modelle angewandt werden können; (4) untersucht die Auswirkung möglicher zukünftiger Klima- und Landnutzungsänderungen auf die europäische Kohlenstoffbilanz anhand von vier verschiedenen illustrativen Szenarien, jeweils unter Berücksichtigung von Klimawandelprojektionen vier verschiedener Klimamodelle. Eine erweiterte Version von LPJ-DGVM findet hierfür Anwendung, die eine umfassende Beschreibung der Hauptlandnutzungstypen beinhaltet.
Die vorliegende Arbeit stellt einen Ansatz vor, um Unsicherheiten in der prozessbasierten Abschätzung von terrestrischen Kohlenstoffbilanzen auf regionaler Skala zu untersuchen und zu reduzieren. Die Ergebnisse dieser Arbeit zeigen, dass der Nettokohlenstoffaustausch zwischen terrestrischer Biosphäre und Atmosphäre unter heutigen klimatischen Bedingungen relativ sicher abgeschätzt werden kann, obwohl erhebliche Unsicherheit über die modelbasierte terrestrische Nettoprimärproduktion existiert. Prozessbasierte Modellierung und Waldbestandsstatistiken wurden erfolgreich kombiniert, um verbesserte Abschätzungen von regionalen Kohlenstoffvorräten und ihrer Änderung mit der Zeit zu ermöglichen. Die Anwendung des angepassten Modells in 77 europäischen Regionen zeigt, dass modellbasierte Abschätzungen des Biomasseaufwuchses in Wäldern weitgehend mit inventarbasierten Abschätzungen für verschiede Baumarten übereinstimmen. Unter Berücksichtigung von historischen Änderungen in Klima, atmosphärischem CO2-Gehalt, Waldfläche und Holzernte (1948-2000) reproduziert das Model auf europäischer Ebene die heutigen, auf Bestandsstatistiken beruhenden, Abschätzungen von Waldaltersstruktur, das Verhältnis von Zuwachs und Entnahme von Biomasse, sowie die Speicherungsraten im Kohlenstoffspeicher der Vegetation. Alternative Szenarien von zukünftigen Landnutzungs- und Klimaänderungen legen nahe, dass die Kohlenstoffaufnahme der europäischen terrestrischen Biosphäre von relevanter Größenordnung für Klimaschutzstrategien sind. Die Speicherungsraten sind jedoch klein im Vergleich zu den absoluten europäischen CO2-Emissionen, und nehmen zudem sehr wahrscheinlich gegen Ende des 21. Jahrhunderts ab. Unsicherheiten in Klimaprojektionen sind eine Hauptursache für die Unsicherheiten in den modellbasierten Abschätzungen des zukünftigen Nettokohlenstoffaustausches und müssen daher in Klimaschutzanalysen der terrestrischen Biosphäre berücksichtigt werden.
Books on the topic "Age of uncertainty"
Uncertainty and insecurity in the New Age. New York, NY: John D. Calandra Italian American Institute, 2009.
Find full textBlatterer, Harry. Coming of age in times of uncertainty. New York: Berghahn Books, 2007.
Find full textParrillo, Vincent N. Uncertainty and insecurity in the New Age. New York, NY: John D. Calandra Italian American Institute, 2009.
Find full textKalemli-Ozcan, Sebnem. Mortality change, the uncertainty effect, and retirement. Cambridge, MA: National Bureau of Economic Research, 2002.
Find full textLove in an age of uncertainty: Reclaiming Aphrodite. London: Aquarian/Thorsons, 1993.
Find full textGritzalis, Dimitris, Sabrina Capitani di Vimercati, Pierangela Samarati, and Sokratis Katsikas, eds. Security and Privacy in the Age of Uncertainty. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-0-387-35691-4.
Full textBailey, James A. Building Learning Capacity in an Age of Uncertainty. New York, NY: Routledge, 2021.: Routledge, 2021. http://dx.doi.org/10.4324/9781003144847.
Full textBook chapters on the topic "Age of uncertainty"
Giritli Nygren, Katarina, Anna Olofsson, and Susanna Öhman. "The Age of Ambivalence." In Critical Studies in Risk and Uncertainty, 1–17. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33524-3_1.
Full textWild, Leah. "Transgressive Terrain: Risk, Otherness and ‘New Age’ Nomadism." In Trust, Risk and Uncertainty, 181–202. London: Palgrave Macmillan UK, 2005. http://dx.doi.org/10.1057/9780230506039_11.
Full textInkster, Nigel. "War in the age of uncertainty." In The World Information War, 281–86. Abingdon, Oxon ; New York, NY : Routledge, [2021] | Series: Routledge advances in defence studies: Routledge, 2021. http://dx.doi.org/10.4324/9781003046905-20.
Full textMonaghan, Philip. "Smarter Interventions in an Age of Uncertainty." In Resilient Cities 2, 391–96. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4223-9_41.
Full textKivinen, Osmo. "Higher Learning in an Age of Uncertainty." In Higher Education Dynamics, 191–206. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-010-0579-1_13.
Full textGreen, Andy. "Young People and Employment: The Age of Uncertainty." In The Crisis for Young People, 45–62. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58547-5_3.
Full textBishop, Christopher. "Embracing Uncertainty: Applied Machine Learning Comes of Age." In Machine Learning and Knowledge Discovery in Databases, 4. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23780-5_3.
Full textChignell, Hugh. "The Age of Uncertainty — Radio in the 1990s." In Public Issue Radio, 173–93. London: Palgrave Macmillan UK, 2011. http://dx.doi.org/10.1057/9780230346451_9.
Full textManor, Ilan, and Corneliu Bjola. "Public Diplomacy in the Age of ‘Post-reality’." In Public Diplomacy and the Politics of Uncertainty, 111–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54552-9_5.
Full textTully, James. "Foreword." In Minority Nations in the Age of Uncertainty, vii—x. Toronto: University of Toronto Press, 2014. http://dx.doi.org/10.3138/9781442621251-001.
Full textConference papers on the topic "Age of uncertainty"
Lewis, P. A. "Continuing education in an age of uncertainty." In Proceedings of SOUTHCON '94. IEEE, 1994. http://dx.doi.org/10.1109/southc.1994.498098.
Full textArmanious, Karim, Sherif Abdulatif, Wenbin Shi, Tobias Hepp, Sergios Gatidis, and Bin Yang. "Uncertainty-Based Biological Age Estimation of Brain MRI Scans." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9414112.
Full textJenkins, Mariah. "MINIMIZING UNCERTAINTY IN ZIRCON AND PLAGIOCLASE AGE DATING FROM DETAILED PETROGRAPHY." In GSA Annual Meeting in Phoenix, Arizona, USA - 2019. Geological Society of America, 2019. http://dx.doi.org/10.1130/abs/2019am-340287.
Full textQian, Yanlin, Ke Chen, Dan Yang, and Joni-Kristian Kamarainen. "Beyond Wisdom of Crowds: Deep Uncertainty Coding for Apparent Age Estimation." In 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC). IEEE, 2019. http://dx.doi.org/10.1109/icivc47709.2019.8981088.
Full textXu, Wenge, Hai-Ning Liang, Kangyou Yu, and Nilufar Baghaei. "Effect of Gameplay Uncertainty, Display Type, and Age on Virtual Reality Exergames." In CHI '21: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3411764.3445801.
Full textChen, Nanxin, Jesus Villalba, Yishay Carmiel, and Najim Dehak. "Measuring Uncertainty in Deep Regression Models: The Case of Age Estimation from Speech." In ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8462416.
Full textWen, Liang, Su Wu, and Xi-Sheng Jia. "Notice of Retraction Age replacement optimization with uncertainty of life time distribution parameters." In 2013 International Conference on Quality, Reliability, Risk, Maintenance and Safety Engineering (QR2MSE). IEEE, 2013. http://dx.doi.org/10.1109/qr2mse.2013.6625660.
Full textSakata, Atsuya, Yasushi Makihara, Noriko Takemura, Daigo Muramatsu, and Yasushi Yagi. "How Confident Are You in Your Estimate of a Human Age? Uncertainty-aware Gait-based Age Estimation by Label Distribution Learning." In 2020 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2020. http://dx.doi.org/10.1109/ijcb48548.2020.9304914.
Full textLiu, Kuan-Hsien, Shuicheng Yan, and C. C. Jay Kuo. "Age group classification via structured fusion of uncertainty-driven shape features and selected surface features." In 2014 IEEE Winter Conference on Applications of Computer Vision (WACV). IEEE, 2014. http://dx.doi.org/10.1109/wacv.2014.6836068.
Full textAhlfeld, Richard, Mauro Carnevale, Simone Salvadori, and Francesco Montomoli. "An Autonomous Uncertainty Quantification Method for the Digital Age: Transonic Flow Simulations Using Multivariate Padé Approximations." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64968.
Full textReports on the topic "Age of uncertainty"
Fraser, Powell A., and Jr. Making the Military Matter in an Age of Uncertainty. Fort Belvoir, VA: Defense Technical Information Center, January 1992. http://dx.doi.org/10.21236/ada437067.
Full textBackus, George A., Thomas Stephen Lowry, Shannon M. Jones, La Tonya Nicole Walker, Barry L. Roberts, and Leonard A. Malczynski. County-Level Climate Uncertainty for Risk Assessments: Volume 25 Appendix X - Forecast Sea Ice Age. Office of Scientific and Technical Information (OSTI), May 2017. http://dx.doi.org/10.2172/1367304.
Full textBackus, George A., Thomas Stephen Lowry, Shannon M. Jones, La Tonya Nicole Walker, Barry L. Roberts, and Leonard A. Malczynski. County-Level Climate Uncertainty for Risk Assessments: Volume 24 Appendix W - Historical Sea Ice Age. Office of Scientific and Technical Information (OSTI), May 2017. http://dx.doi.org/10.2172/1367443.
Full textBunnell, F. L. Alchemy and uncertainty: What good are models? Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1989. http://dx.doi.org/10.2737/pnw-gtr-232.
Full textHansen, Lars Peter, and Thomas Sargent. Macroeconomic Uncertainty Prices when Beliefs are Tenuous. Cambridge, MA: National Bureau of Economic Research, April 2019. http://dx.doi.org/10.3386/w25781.
Full textBinh T. Pham, Jeffrey J. Einerson, and Grant L. Hawkes. Uncertainty Quantification of Calculated Temperatures for the AGR-1 Experiment. Office of Scientific and Technical Information (OSTI), March 2013. http://dx.doi.org/10.2172/1082396.
Full textBinh T. Pham, Jeffrey J. Einerson, and Grant L. Hawkes. Uncertainty Quantification of Calculated Temperatures for the AGR-1 Experiment. Office of Scientific and Technical Information (OSTI), April 2012. http://dx.doi.org/10.2172/1044210.
Full textJulio-Román, Juan Manuel. How uncertain are NAIRU estimates in Colombia? Bogotá, Colombia: Banco de la República, August 2001. http://dx.doi.org/10.32468/be.184.
Full textPham, Binh Thi-Cam. Uncertainty Quantification of Calculated Temperatures for the AGR 3/4 Experiment. Office of Scientific and Technical Information (OSTI), September 2015. http://dx.doi.org/10.2172/1244623.
Full textEinav, Liran, Amy Finkelstein, Iuliana Pascu, and Mark Cullen. How general are risk preferences? Choices under uncertainty in different domains. Cambridge, MA: National Bureau of Economic Research, January 2010. http://dx.doi.org/10.3386/w15686.
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