Relevant bibliographies by topics / Faires

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Faires'

Author: Grafiati
Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Faires"

1

Stöberl. "Dolmetscher, faires Asylverfahren." Juristische Blätter 129, no. 6 (June 2007): 399–401. http://dx.doi.org/10.1007/s00503-007-1190-9.

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Lewisch, Peter. "Geschworenengerichtsbarkeit und faires Verfahren." Juristische Blätter 134, no. 8 (August 2012): 496–502. http://dx.doi.org/10.1007/s00503-012-0063-z.

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Lewisch, Peter. "Geschworenengerichtsbarkeit und faires Verfahren." Juristische Blätter 134, no. 8 (2012): 496–502. http://dx.doi.org/10.33196/jbl201208049601.

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Hutzler, Florian, and Nicole Himmelstoß. "Austrian NeuroCloud: FAIRes und vertrauenswürdiges Forschungsdatenmanagement." Zeitschrift für Hochschulentwicklung 19, Sonderheft Administration (February 5, 2024): 117–42. http://dx.doi.org/10.21240/zfhe/sh-a/08.

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Der FAIRe Umgang mit Forschungsdaten ist wichtig für deren langfristigen Werterhalt und Nutzbarkeit sowie für Transparenz und Offenheit in Wissenschaft und Forschung. Für ein nachhaltiges Forschungsdatenmanagement an Universitäten ist die Etablierung von domänenspezifischen, FAIR-konformen und vertrauenswürdigen Datenrepositorien unabdingbar. In diesem Beitrag werden am Beispiel des Austrian-NeuroCloud-Projekts die Herausforderungen für deren Implementierung beschrieben und mögliche Lösungsansätze aufgezeigt. Die Einbettung in den universitären Entwicklungsplan und die finanzielle Absicherung im Rahmen der Leistungsvereinbarungen sind essentiell für die langfristige Absicherung.
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Touval, Ayana. "Investigating a Definite Integral—from Graphing Calculator to Rigorous Proof." Mathematics Teacher 90, no. 3 (March 1997): 230–32. http://dx.doi.org/10.5951/mt.90.3.0230.

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Beclin, Katharina. "Garantieren die Verteidigungsrechte von Jugendlichen ein faires Verfahren?" Zeitschrift für kritik - recht - gesellschaft, no. 2 (2021): 226. http://dx.doi.org/10.33196/juridikum202102022601.

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Mönch, Axel. "„Ausnahmen im Wettbewerbsrecht würden ein faires Marktumfeld schaffen“." agrarzeitung 76, no. 30 (2021): 54. http://dx.doi.org/10.51202/1869-9707-2021-30-054.

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Kramer, M. J. "Well Met: Renaissance Faires and the American Counterculture." Journal of American History 100, no. 4 (March 1, 2014): 1290–91. http://dx.doi.org/10.1093/jahist/jau142.

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Wood, Juliette. "Well Met: Renaissance Faires and the American Counterculture." Folklore 127, no. 1 (January 2, 2016): 118–19. http://dx.doi.org/10.1080/0015587x.2015.1129786.

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Riley, James. "Well met: Renaissance Faires & the American counterculture." Studies in Theatre and Performance 34, no. 2 (May 4, 2014): 184–86. http://dx.doi.org/10.1080/14682761.2014.906952.

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Dissertations / Theses on the topic "Faires"

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Haase, Katrin. "Die Anforderungen an ein faires Gerichtsverfahren auf europäischer Ebene." Taunusstein Driesen, 2006. http://www.driesen-online.de/gv_haase_anforderungen.htm.

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Gaede, Karsten. "Fairness als Teilhabe - Das Recht auf konkrete und wirksame Teilhabe durch Verteidigung gemäss Art. 6 EMRK : ein Beitrag zur Dogmatik des fairen Verfahrens in europäischen Strafverfahren und zur wirksamkeitsverpflichteten Konventionsauslegung /." [S.l.] : [s.n.], 2006. http://aleph.unisg.ch/hsgscan/hm00189701.pdf.

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Stegmann, Andreas [Verfasser]. "Unternehmenssanktionen durch die Weltbank : Betrug, Korruption und faires Verfahren / Andreas Stegmann." Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften, 2017. http://d-nb.info/1148910816/34.

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Milej, Tomasz. "Rechtsprechung als Dialog zur Entwicklung des Rechts auf ein faires Strafverfahren in der polnischen Verfassungsrechtsprechung mit Blick auf die Entscheidungspraxis des EGMR und ausländischer Verfassungsgerichte." Berlin BWV, Berliner Wiss.-Verl, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2988484&prov=M&dok_var=1&dok_ext=htm.

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Hies, Johannes. "Das fair-trial-Prinzip und seine Bindungswirkung für den Rechtsanwalt als Strafverteidiger /." Berlin : Dissertation.de, 2009. http://d-nb.info/995272301/04.

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Schleiminger, Dorrit. "Konfrontation im Strafprozess : Art. 6 Ziff. 3 lit. d EMRK mit besonderer Berücksichtigung des Verhältnisses zum Opferschutz im Bereich von Sexualdelikten gegen Minderjährige /." Basel [u.a.] : Helbing & Lichtenhahn, 2001. http://www.gbv.de/dms/sbb-berlin/322849780.pdf.

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Stabel, Julie. "Der Anspruch auf angemessene Dauer eines verwaltungsgerichtlichen Verfahrens /." Hamburg : Kovač, 2006. http://www.verlagdrkovac.de/3-8300-2564-5.htm.

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Gordon-Vrba, Lucy. "Vielparteienprozesse : kollektive Durchsetzung gleichartiger, individueller Kompensationsansprüche unter dem Aspekt der prozessualen Effizienz und Fairness /." Zürich ; Basel Genf : Schulthess, 2007. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017383618&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Herzog, Ruth. "Art. 6 EMRK und kantonale Verwaltungsrechtspflege /." Bern : Stämpfli, 1995. http://www.ub.unibe.ch/content/bibliotheken_sammlungen/sondersammlungen/dissen_bestellformular/index_ger.html.

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Sieber, André [Verfasser], and Jörg [Akademischer Betreuer] Nolte. "Energiemanagement für drahtlose tief eingebettete Systeme : Feingranulares, faires Management zum Erreichen von Lebenszeitzielen bei knappen Energieressourcen / André Sieber ; Betreuer: Jörg Nolte." Cottbus : BTU Cottbus - Senftenberg, 2016. http://d-nb.info/1114666866/34.

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Books on the topic "Faires"

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Schmidt, Phillip, and David Ruppel. Student study guide for Calculus, second edition, [by] J. Douglas Faires and Barbara T. Faires. 2nd ed. New York: Random House, 1988.

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Albin, Eser, Meyer Jürgen 1936-, Germany (West). Bundesministerium der Justiz., and Max-Planck-Institut für Ausländisches und Internationales Strafrecht., eds. Öffentliche Vorverurteilung und faires Strafverfahren: Eine rechtsvergleichende Untersuchung im Auftrag des Bundesministeriums der Justiz. Freiburg i. Br: Eigenverlag Max-Planck-Institut für Ausländisches und Internationales Strafrecht, 1986.

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Cherryh, C. J. The dreamstone. London: VGSF, 1987.

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Barry, Brian M. Justice as impartiality. Oxford: Clarendon, 1995.

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Claude, Kaufmann Jean, ed. Faire ou faire-faire?: Famille et services. Rennes: Presses universitaires de Rennes, 1996.

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Board, Canada Treasury. Make or buy? =: Faire ou faire faire? Ottawa, Ont: Treasury Board of Canada = Conseil du trésor du Canada, 1995.

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Guiley, Rosemary. Fairies. New York: Chelsea House Publishers, 2010.

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Guiley, Rosemary. Fairies. New York: Chelsea House Publishers, 2010.

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Levine, Gail Carson. Fairest. New York: Scholastic, 2008.

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Hoffman, Nancy. Fairies. San Diego: Lucent Books, 2004.

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Book chapters on the topic "Faires"

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Holinshed, Raphaell, William Harrison, John Hooker, and Vowell. "Of Faires and Markets." In Chronicles, 339–42. London: Routledge, 2022. http://dx.doi.org/10.4324/9781315020716-43.

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Kaufmann, Frank. "Faires Angebot oder übles Foul?" In Grenzen der Demokratie, 187–213. Wiesbaden: VS Verlag für Sozialwissenschaften, 2012. http://dx.doi.org/10.1007/978-3-531-19682-4_16.

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Manz, Olaf. "Faires Mischen bei vielen Spielkarten." In Wahrscheinliche Algebra, 159–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63748-7_18.

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Petersen, Holger. "Effizientes faires Geld mit skalierbarer Sicherheit." In Verläßliche IT-Systeme, 139–50. Wiesbaden: Vieweg+Teubner Verlag, 1997. http://dx.doi.org/10.1007/978-3-322-86842-8_10.

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Holinshed, Raphaell, William Harrison, John Hooker, and Vowell. "Of Our Principall Faires and Markets." In Chronicles, 411–13. London: Routledge, 2022. http://dx.doi.org/10.4324/9781315020716-66.

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Fastermann, Petra. "Messen zu 3D-Druck und Maker Faires." In 3D-Drucken, 61–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-46094-8_9.

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Fastermann, Petra. "Messen zu 3D-Druck und Maker Faires." In 3D-Drucken, 65–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49866-8_9.

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Richter, Sebastian, and Erich Heumüller. "Ansatz für ein faires Beteiligungsmodell am Datenerlös." In Marktforschung für die Smart Data World, 85–98. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-28664-4_7.

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Berka, Walter. "Das Recht auf ein faires gerichtliches Verfahren." In Lehrbuch Grundrechte, 175–87. Vienna: Springer Vienna, 2000. http://dx.doi.org/10.1007/978-3-7091-6776-2_29.

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Henze, Norbert, Kai Müller, and Judith Schilling. "Ein faires Glücksrad mit unterschiedlich großen Sektoren." In Stochastik rezeptfrei unterrichten, 57–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-62744-0_4.

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Conference papers on the topic "Faires"

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Shekhar, Shubhranshu, Neil Shah, and Leman Akoglu. "FairOD: Fairness-aware Outlier Detection." In AIES '21: AAAI/ACM Conference on AI, Ethics, and Society. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3461702.3462517.

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Gu, Bin, Zhou Zhai, Xiang Li, and Heng Huang. "Towards Fairer Classifier via True Fairness Score Path." In CIKM '22: The 31st ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3511808.3557109.

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Luo, Renqiang, Huafei Huang, Shuo Yu, Xiuzhen Zhang, and Feng Xia. "FairGT: A Fairness-aware Graph Transformer." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/50.

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The design of Graph Transformers (GTs) often neglects considerations for fairness, resulting in biased outcomes against certain sensitive subgroups. Since GTs encode graph information without relying on message-passing mechanisms, conventional fairness-aware graph learning methods are not directly applicable to address these issues. To tackle this challenge, we propose FairGT, a Fairness-aware Graph Transformer explicitly crafted to mitigate fairness concerns inherent in GTs. FairGT incorporates a meticulous structural feature selection strategy and a multi-hop node feature integration method, ensuring independence of sensitive features and bolstering fairness considerations. These fairness-aware graph information encodings seamlessly integrate into the Transformer framework for downstream tasks. We also prove that the proposed fair structural topology encoding with adjacency matrix eigenvector selection and multi-hop integration are theoretically effective. Empirical evaluations conducted across five real-world datasets demonstrate FairGT's superiority in fairness metrics over existing graph transformers, graph neural networks, and state-of-the-art fairness-aware graph learning approaches.
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Xie, Junsong, Yonghui Yang, Zihan Wang, and Le Wu. "Learning Fair Representations for Recommendation via Information Bottleneck Principle." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/273.

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User-oriented recommender systems (RS) characterize users' preferences based on observed behaviors and are widely deployed in personalized services. However, RS may unintentionally capture biases related to sensitive attributes (e.g., gender) from behavioral data, leading to unfair issues and discrimination against particular groups (e.g., females). Adversarial training is a popular technique for fairness-aware RS, when filtering sensitive information in user modeling. Despite advancements in fairness, achieving a good accuracy-fairness trade-off remains a challenge in adversarial training. In this paper, we investigate fair representation learning from a novel information theory perspective. Specifically, we propose a model-agnostic Fair recommendation method via the Information Bottleneck principle FairIB. The learning objective of FairIB is to maximize the mutual information between user representations and observed interactions, while simultaneously minimizing it between user representations and sensitive attributes. This approach facilitates the capturing of essential collaborative signals in user representations while mitigating the inclusion of unnecessary sensitive information. Empirical studies on two real-world datasets demonstrate the effectiveness of the proposed FairIB, which significantly improves fairness while maintaining competitive recommendation accuracy, either in single or multiple sensitive scenarios. The code is available at https://github.com/jsxie9/IJCAI_FairIB.
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Guo, Huizhong, Jinfeng Li, Jingyi Wang, Xiangyu Liu, Dongxia Wang, Zehong Hu, Rong Zhang, and Hui Xue. "FairRec: Fairness Testing for Deep Recommender Systems." In ISSTA '23: 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3597926.3598058.

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Chakraborty, Mithun, Ulrike Schmidt-Kraepelin, and Warut Suksompong. "Picking Sequences and Monotonicity in Weighted Fair Division." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/12.

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We study the problem of fairly allocating indivisible items to agents with different entitlements, which captures, for example, the distribution of ministries among political parties in a coalition government. Our focus is on picking sequences derived from common apportionment methods, including five traditional divisor methods and the quota method. We paint a complete picture of these methods in relation to known envy-freeness and proportionality relaxations for indivisible items as well as monotonicity properties with respect to the resource, population, and weights. In addition, we provide characterizations of picking sequences satisfying each of the fairness notions, and show that the well-studied maximum Nash welfare solution fails resource- and population-monotonicity even in the unweighted setting. Our results serve as an argument in favor of using picking sequences in weighted fair division problems.
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Lima, Luiz Fernando F. P. de, Danielle Rousy D. Ricarte, and Clauirton A. Siebra. "Assessing Fair Machine Learning Strategies Through a Fairness-Utility Trade-off Metric." In Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/eniac.2021.18288.

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Due to the increasing use of artificial intelligence for decision making and the observation of biased decisions in many applications, researchers are investigating solutions that attempt to build fairer models that do not reproduce discrimination. Some of the explored strategies are based on adversarial learning to achieve fairness in machine learning by encoding fairness constraints through an adversarial model. Moreover, it is usual for each proposal to assess its model with a specific metric, making comparing current approaches a complex task. In that sense, we defined a utility and fairness trade-off metric. We assessed 15 fair model implementations and a baseline model using this metric, providing a systemically comparative ruler for other approaches.
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Hossain, Safwan, Andjela Mladenovic, and Nisarg Shah. "Designing Fairly Fair Classifiers Via Economic Fairness Notions." In WWW '20: The Web Conference 2020. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3366423.3380228.

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Vasquez Verdugo, Jonathan, Xavier Gitiaux, Cesar Ortega, and Huzefa Rangwala. "FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context." In LAK22: 12th International Learning Analytics and Knowledge Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3506860.3506902.

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Biswas, Soumita, Anuran Mitra, Sovan Mistry, Trisha Roy Chowdhury, Soumodip Sinha, Ani Biswas, and Raja Karmakar. "FairIN: Throughput Fairness in Infrastructure-Based Wireless Access Networks." In 2020 International Conference on System, Computation, Automation and Networking (ICSCAN). IEEE, 2020. http://dx.doi.org/10.1109/icscan49426.2020.9262313.

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Reports on the topic "Faires"

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Smiegocki, Victoria, Pamela R. Metzger, and Andrew L. B. Davies. Fewer, Not Fairer. SMU Dedman School of Law, November 2021. http://dx.doi.org/10.25172/dc.4.

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In 2019, police across Dallas County asked the District Attorney to prosecute fewer marijuana cases than the year before. This report examines whether the racial disparity in those cases improved at the same time. Fewer, Not Fairer shows that while the number of referrals declined, police were still more likely to refer a Black person for marijuana prosecution than a non-Black person. However, some cities achieved more fairness when their police departments almost entirely stopped requesting marijuana prosecutions altogether.
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Herz, Holger, and Dmitry Taubinsky. What Makes a Price Fair? An Experimental Analysis of Transaction Experience and Endogenous Fairness Views. Cambridge, MA: National Bureau of Economic Research, October 2016. http://dx.doi.org/10.3386/w22728.

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Unterhitzenberger, Christine, and Kate Lawrence. Fairness and unfairness in projects: A study exploring what individuals perceive as fair or unfair treatment. Association for Project Management, August 2022. http://dx.doi.org/10.61175/ejnb1873.

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“Life is not fair, get used to it” – A quote often attributed to Bill Gates, but originally by Charles J. Sykes, which we believe should be challenged. Life should not be about getting used to unfairness, but about how we can create an environment that provides a fairer experience for everyone. The motivation for this is not only about being good and decent humans, but also about the negative impact unfair treatment has on individuals, organisations and projects. This study, conducted by Christine Unterhitzenberger and Kate Lawrence (both University of Leeds), explores what individuals perceive as fair or unfair treatment in projects, which factors influence their perceptions and subsequent behaviours and how these impact individuals, organisations and projects.
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Guinto, Renzo R. Making global health greener, fairer, and younger. Edited by Chris Bartlett. Monash University, November 2022. http://dx.doi.org/10.54377/f2c3-33a3.

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Granja, Joao, Gregor Matvos, and Amit Seru. Selling Failed Banks. Cambridge, MA: National Bureau of Economic Research, August 2014. http://dx.doi.org/10.3386/w20410.

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Söding, Emanuel. Die Dateninfrastruktur (DIS)-Erhebung im Forschungsbereich Erde und Umwelt der Helmholtz-Gemeinschaft: Erste Ergebnisse und Schlussfolgerungen. HMC Office, GEOMAR Helmholtz Centre for Ocean Research Kiel, 2022. http://dx.doi.org/10.3289/hmc_publ_06.

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Die Anschlussfähigkeit bestehender Helmholtz-Dateninfrastrukturen an nationale und internationale Initiativen (z.B. NFDI, EOSC und andere), ist ein wichtiges zentren-übergreifendes Ziel der Helmholtz- Gemeinschaft. Dafür ist es entscheidend, die bestehenden Zusammenhänge der Forschungsdaten- erhebenden und -nachnutzenden sowie die Dateninfrastrukturen (DIS) entlang der FAIR-Prinzipien1 zu ordnen. Ziel dieser Erhebung ist es, einen Überblick über bestehende Praktiken und Entwicklungs- stände der Dateninfrastrukturen (DIS) in der Helmholtz Gemeinschaft im Bereich Erde und Umwelt zu erhalten, um eine konsistente Strategie zur Umsetzung eines FAIRen Datenraumes entwickeln zu können.
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Karn, P., and W. Simpson. ICMP Security Failures Messages. RFC Editor, March 1999. http://dx.doi.org/10.17487/rfc2521.

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THIELGES, J. R. FAILED FUEL DISPOSITION STUDY. Office of Scientific and Technical Information (OSTI), December 2004. http://dx.doi.org/10.2172/836350.

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Jenkins, Cody David. Predicting and Preventing Failures. Office of Scientific and Technical Information (OSTI), July 2019. http://dx.doi.org/10.2172/1545743.

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MacDonald, P. E., V. N. Shah, L. W. Ward, and P. G. Ellison. Steam generator tube failures. Office of Scientific and Technical Information (OSTI), April 1996. http://dx.doi.org/10.2172/236258.

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