A Method for Estimating the Accuracy of Individual Control Question Tests

2019 ◽  
pp. 142-147
Author(s):  
Gordon H. Barland
Keyword(s):  
Individual Control ◽  
Control Question

Validity of Outside-Issue Questions in the Control Question Test

2000 ◽  
Author(s):  
Charles R. Honts ◽  
Susan Amato ◽  
Anne Gordon
Keyword(s):  
Control Question

Analysis and control of the paper moisture content variability by using fuzzy and traditional individual control charts

2021 ◽  
Vol 208 ◽  
pp. 104211
Author(s):  
José L. Rodríguez-Álvarez ◽  
Rogelio López-Herrera ◽  
Iván E. Villalon-Turrubiates ◽  
Rey D. Molina-Arredondo ◽  
Jorge L. García Alcaraz ◽  
...  
Keyword(s):  
Moisture Content ◽  
Control Charts ◽  
Individual Control ◽  
And Control

scholarly journals Unequal chances: ex ante fairness and individual control

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Leticia Micheli ◽  
Nickolas Gagnon
Keyword(s):  
Perceived Control ◽  
Online Survey ◽  
Family Income ◽  
Financial Outcomes ◽  
Individual Control ◽  
Ex Ante ◽  
And Gender ◽  
Different Sources ◽  
Do So

AbstractUnequal financial outcomes often originate from unequal chances. Yet, compared to outcomes, little is known about how individuals perceive unequal distributions of chances. We investigate empirically the role of different sources of unequal chances in shaping inequality perceptions. Importantly, we do so from an ex ante perspective—i.e., before the chances are realized—which has rarely been explored. In an online survey, we asked uninvolved respondents to evaluate ex ante the fairness of unequal allocations of chances. We varied the source of inequality of chances, using a comprehensive range of factors which resemble several real world situations. Respondents also evaluated how much control individuals hold over the distribution of chances. Results show that different sources generate different ex ante perception of fairness. That is, unequal chances based on socioeconomic and biological factors, such as gender, family income and ethnicity, are evaluated to be unfair relative to the same chances based on effort, knowledge, and benevolence. Results also show that, for most individuals, there is a positive correlation between perceived control of a factor and fairness of unequal chances based on that factor. Luck appears to be an exception to this correlation, ranking as high in fairness as effort, knowledge, and benevolence, but similarly low in individual control as ethnicity, family income, and gender.

A control question test oriented towards students

1999 ◽  
Vol 6 (2) ◽  
pp. 114-115
Author(s):  
M.T Bradley ◽  
M.E Black
Keyword(s):  
Control Question

Individual control treatment in split-plot experiments

2009 ◽  
Vol 50 (4) ◽  
pp. 697-710 ◽  
Author(s):  
Are Halvor Aastveit ◽  
Trygve Almøy ◽  
Iwona Mejza ◽  
Stanislaw Mejza
Keyword(s):  
Control Treatment ◽  
Individual Control ◽  
Split Plot

scholarly journals Public Interest, Health Research and Data Protection Law: Establishing a Legitimate Trade-Off between Individual Control and Research Access to Health Data

Laws ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Mark J. Taylor ◽  
Tess Whitton
Keyword(s):  
Public Interest ◽  
Data Protection ◽  
Health Research ◽  
Health Data ◽  
Personal Health ◽  
Positive Contribution ◽  
Data Governance ◽  
The Public ◽  
Individual Control ◽  
Data Protection Law

The United Kingdom’s Data Protection Act 2018 introduces a new public interest test applicable to the research processing of personal health data. The need for interpretation and application of this new safeguard creates a further opportunity to craft a health data governance landscape deserving of public trust and confidence. At the minimum, to constitute a positive contribution, the new test must be capable of distinguishing between instances of health research that are in the public interest, from those that are not, in a meaningful, predictable and reproducible manner. In this article, we derive from the literature on theories of public interest a concept of public interest capable of supporting such a test. Its application can defend the position under data protection law that allows a legal route through to processing personal health data for research purposes that does not require individual consent. However, its adoption would also entail that the public interest test in the 2018 Act could only be met if all practicable steps are taken to maximise preservation of individual control over the use of personal health data for research purposes. This would require that consent is sought where practicable and objection respected in almost all circumstances. Importantly, we suggest that an advantage of relying upon this concept of the public interest, to ground the test introduced by the 2018 Act, is that it may work to promote the social legitimacy of data protection legislation and the research processing that it authorises without individual consent (and occasionally in the face of explicit objection).

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