Fairness definition

Fairness means treating the crime victim reasonably, even-handedly, and impartially.

Fairness also means that the data subject cannot be forced to give data on himself or to accept that data on him is being processed. Data controllers cannot misuse the information they might have. This requirement is also noticeable in the provision on the “consent” which sometimes must be given by the data subject in order to collect or process data on him. This consent must be given “freely”.

Fairness in SHAPES means that data subject’s data is processed in a way that individuals could reasonably expect and that it can be explained as to why the data is processed differently. Also, when developing services, SHAPES will consider how the processing may affect individuals. If any adverse impacts are detected, SHAPES will first try to find an option that does not cause harm to individuals. If there is no alternative solution, the potential adverse impact will be justified and explained. In practice, this analysis will be done as part of DPIA.

Examples of Fairness in a sentence

• The Congressional Review Act, 5U.S.C. 801 et seq., as added by the Small Business Regulatory Enforcement Fairness Act of 1996, generally provides that before a rule may take effect, the agency promulgating the rule must submit a rule report, which includes a copy of the rule, to each House of the Congress and to the Comptroller General of the United States.

• Under section 213(a) of the Small Business Regulatory Enforcement Fairness Act of 1996 (Pub.

• Fairness and transparency in the tender process require that the firms or their Affiliates competing for a specific assignment do not derive a competitive advantage from having provided consulting services related to this tender.

• The Small Business and Regulatory Enforcement Ombudsman and 10 regional Fairness Boards were established to receive comments from small businesses about Federal agency enforcement activities and rate each agency’s responsiveness to small business.

• You may ask the Court for permission to speak at the Fairness Hearing.

More Definitions of Fairness

Fairness means applying the rules of the tender equally to all participants

Fairness means ensuring (i) equal opportunity for and treatment for eligible bidders; (ii) equitable distribution of rights and obligations between borrowers and providers of goods, works, and services; and (iii) credible mechanisms for addressing procurement-related complaints and providing recourse.

Fairness means that the owner must not use undisclosed criteria when evaluating a bid

Fairness to those in employment.89 The means employed in pursuit of these objectives have generated considerable hostility from civil society campaign groups90 and from devolved governments. If the most vocal opposition has arguably come from Scotland’s governing Scottish National Party,91 of the devolved regions only Northern Ireland is currently in a position to translate its concerns about UK government policy into a distinctive regional approach.92 However, given the long-established convention that the region’s social security system mirror that in Great Britain, underpinned by its weak fiscal position and the statutory requirement to consult the UK government on the desirability of maintaining common provision,93 a compelling case would have to be made for any significant policy divergence. The extent to which such a case can be made may depend in large measure on the implementation of the human rights provisions of the Agreement.

Fairness. Opinion” Section 3.23 “Government Contracts” Section 3.15(a) “HIPAA” Section 3.7 “Independent Directors” Section 3.14(c)

Fairness generally means you must not process personal data in a way that is unduly detrimental, unexpected or misleading to the individuals concerned. It also requires you to be, where appropriate, clear and open with individuals about how you use their information, in keeping with their reasonable expectations.

Fairness means (mathematically), which in this case is a decision made by technical experts without any political accountability, one hidden in a completely non- transparent algorithmic ‘black box’ and one that is of crucial ethical significance.