Fairness
Fairness - Related Videos
14:32
Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care
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Cited by 26 •
2011
This paper illustrates an innovative visual approach (photovoice or photo-elicitation) to achieve fair process in clinical care for patients living with chronic health conditions, illuminate gaps in clinical knowledge, forge better therapeutic relationships, and identify patient-centered goals and possibilities for healing.
01:22
Fair Value Principle
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2025
The fair value principle in accounting mandates measuring and reporting assets and liabilities at their current market value rather than their historical purchase cost. This principle aims to present a more accurate and timely reflection of an entity’s financial position, particularly in environments characterized by fluctuating market conditions. Fair value accounting is especially relevant for financial instruments and other assets whose values are sensitive to market dynamics.Under fair...
01:29
Cost Basis vs. Fair Value Accounting
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2025
Cost basis and fair value accounting represent two contrasting methods for valuing assets, each with distinct implications for financial reporting and decision-making. These methods not only influence how companies report their financial position but also affect investor perceptions and regulatory compliance.Cost basis accounting relies on the historical cost principle, meaning assets are recorded at their acquisition price and remain unchanged over time unless impaired. This approach is valued...
10:38
Human Fear Conditioning Conducted in Full Immersion 3-Dimensional Virtual Reality
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Cited by 25 •
2010
Classical fear conditioning paradigm was adapted for human participants in a fully immersive virtual reality setting. Using a discrimination paradigm, conditioned fear, cue and context memory retention, and extinction was measured with skin conductance response to dynamic virtual snakes and spiders (the conditioned stimuli) in two distinct virtual contexts.
09:15
Creating the Minimal Group Paradigm
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2023
Source: Julian Wills & Jay Van Bavel—New York University The study of intergroup relations, such as prejudice, conflict, and discrimination, has always been a central topic in social psychology. Does discrimination stem from competition with other groups, a history of conflict, or derogatory stereotypes? Despite an abundance of real-world examples, the ingredients that lead to intergroup discrimination are often unclear. To help solve this problem, a group of psychologists created "minimal...
FAQs
Evaluation starts by examining whether patient characteristics, social conditions, data quality, or decision rules are associated with unequal outcomes. The key question is not simply whether groups differ, but whether those differences are justified within the clinical or research context. This analysis can expose hidden bias and identify where care or access needs correction.
Decision rules can produce unequal effects even when they are applied consistently. A rule may interact with patient characteristics, social conditions, or weaknesses in the underlying data, creating differences in diagnosis, treatment, or resource access. Reviewing the rule together with its consequences helps distinguish procedural consistency from outcomes that are ethically unjustified.
Poor or uneven data can distort how clinical evidence represents different populations. If data do not adequately reflect relevant patient characteristics or social conditions, an evaluation may miss unequal outcomes or misinterpret them. Fairness review therefore treats data quality as part of the decision process, rather than as a separate technical concern.
Evidence should be examined for whether its conclusions apply consistently across the populations affected by a decision. Attention to patient characteristics, social conditions, and data quality can reveal when apparently general findings conceal unequal effects. This approach supports more careful interpretation and helps clinicians and researchers avoid treating limited evidence as universally reliable.
A practical review begins by identifying the affected patient groups, relevant social conditions, data sources, and decision rules. The team then examines whether these elements correspond with unequal care, diagnosis, treatment, access, or participation. If unjustified differences appear, the process can be revised and documented more transparently to support consistent and ethically responsible decisions.
Fairness becomes particularly important when researchers or clinicians must allocate limited resources and establish decision priorities. Reviewing patient characteristics, social conditions, available data, and the consequences of allocation rules can reveal unequal effects. Such scrutiny helps make resource decisions more transparent and supports trust in how scarce clinical opportunities are distributed.
Study design should consider whether different populations have equitable opportunities to participate and whether the resulting evidence represents those populations adequately. Reviewing participation alongside patient characteristics, social conditions, and data quality can identify gaps that weaken interpretation. Addressing these issues improves the relevance of findings and supports more responsible clinical research.