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What is Fairness

Encyclopedia of Strategic Leadership and Management
A salient action by which followers, in-person or cyber, perceive leaders as working within the rules or standards for correct practice or conduits within a profession.
Published in Chapter:
Leadership Shifts: Perceptions and Consequences, In-Person, or Cyber
Sharon L. Burton (Florida Institute of Technology, USA)
Copyright: © 2017 |Pages: 27
DOI: 10.4018/978-1-5225-1049-9.ch028
Abstract
This text examines the perception and consequences of new overall leaders whether in-person or cyber. First, the researcher presents fairness as a salient action by which followers, in-person or cyber, perceive leaders as working within the rules or standards for correct practice or conduits within a profession. Second, the researcher utilizes the fairness supposition to present leadership behaviors in that followers are generally willing to be led. Third, the researcher compares the fairness definition and supposition to a case study. Finally, the researcher presents how the values that brace leaders' fairness behaviors affect the behaviors of their followers and walk through behaviors and thoughts that may surface. The information will provide data that practitioners, and academes may employ in long and short term, in-person and cyber strategies.
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Teaching and Assessing Data Literacy for Adolescent Learners
The degree of how the interpretation or use of an assessment is not affected by characteristics of test-takers that are irrelevant to the construct.
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Using Peer Feedback to Motivate Teamwork in an Online Learning Environment
an ethical approach or quality, ensuring that students are treated in the right way.
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Ethical Considerations for Artificial Intelligence in Educational Assessments
This ethics principle relates to fair, equitable and appropriate educational practices that should be perpetuated by AI systems.
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Certifications for Medical Interpreters: A Comparative Analysis
refers to providing equal unbiased opportunity to each candidate in the process ( equity, parity )
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Academic Integrity in Online Foreign Language Assessment: What Does Current Research Tell Us?
The concept that considers each learner’s needs and characteristics so as to treat them in a suitable, objective, and equal way while assessing their skills and knowledge. To achieve fairness, reliable and valid assessment is needed.
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AI and Social Impact: A Review of Current Use Cases and Broader Implications
The equal treatment of all without favoring one. Taking into account all sides to ensure decisions are based off impartial data and not favoring one group over another.
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Evaluation in Specialized Translation Teaching: A New Method for Grading Scientific and Technical Translation Compulsory Activities
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Open Challenges and Research Issues of XAI in Modern Smart Cities
The property of an AI system that ensures that its outcomes are not systematically biased against certain groups of people, and do not perpetuate existing social inequalities.
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Beyond Tools and Procedures: The Role of AI Fairness in Responsible Business Discourse
To be distinguished between the sociological and the mathematical meaning. From the sociological perspective, fairness defines the way some people are being treated in a society and it is heavily based on ethical values.
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Creating Diverse, Equitable, and Inclusive Digital Learning Platforms for Young Children
Absence of prejudice or favoritism toward an individual or group that provides a leveled playing field regardless of inherent differences.
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Trust and Fairness Management in P2P and Grid Systems
Measure used to determine whether agents are receiving a fair share of a resources.
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Critical Success Factors for Distance Education Programs
A subjective term defining the level to which a student feels he or she was treated fairly by the professor with respect to the class, including but not limited to test questions, grading, schedule flexibility, and so forth.
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Appreciation Level and Organizational Performance
Fairness in this chapter is defined in two aspects: fairness-1 signifies how subjects feel about team performance evaluation; and fairness-2 means how subjects feel about individual effort-demand fairness (Janssen, 2001; Siegrist, 1996) by preparing 14 questionnaire items with a four-point scale: totally disagree to totally agree.
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Comprehending Algorithmic Bias and Strategies for Fostering Trust in Artificial Intelligence
The concept of fairness varies across disciplines, and there is no universally accepted definition. Developers struggle to express fairness in mathematical terms, and there are trade-offs between different definitions, making it challenging for businesses to adopt a specific definition ( Silberg & Manyika, 2019 ).
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ChatGPT and Other Generative AI Tools in Education: Transformative Potential and Ethical Considerations
Ensuring that AI systems and their outcomes do not disproportionately favor or discriminate against particular groups of people.
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