Virginia Winter : This Is An Un Official Fan Site Tribute
Virginia Winter Susan Strong, Monica Wells, Connie Burbett, Victoria Winter
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Virginia Winter

Movie Title Year Distributor Notes Rev Formats All The Senator's Girls 1977 VCX Anal 1 DRO Black Silk Stockings 1979 Select-a-tape DRO Blue Vanities 16 1987 Blue Vanities DO Classic Swedish Erotica 10 1986 Unknown Facial Classic Swedish Erotica 13 1986 Unknown Danish Films 1143 1978 Unknown Liberation of Honeydoll Jones 1977 VCX 1 DO Rene Bond: Sex Kitten 2004 Alpha Blue Archives DRO Roommates 2000 Blue Vanities DRO Sexy In Sepia 2 2012 Global Media International DRO Sheer Panties 1978 Essex Video / Electric Hollywood Facial Clip O Stormy 1980 Metro NonSex Clip 1 DRO Swedish Erotica 1 1981 Caballero Home Video 1 R Swedish Erotica 4Hr 2 2003 Caballero Classics DO Swedish Erotica Film 030 1978 Caballero Home Video Swedish Erotica Film 031 1978 Caballero Home Video Facial Swedish Erotica Film 052 1978 Caballero Home Video CumSwap O Swedish Erotica Film 059 1978 Caballero Home Video Facial O Swedish Erotica Film 061 1978 Caballero Home Video LezOnly O Swedish Erotica Film 091 1978 Caballero Home Video Facial Swedish Erotica Film 092 1978 Caballero Home Video Facial Swedish Erotica Film 126 1978 Caballero Home Video Swedish Erotica Hard 15 1993 Odyssey D Swedish Erotica Hard 22 1993 Odyssey Facial D Teenage Fantasies 2 1977 Arrow Productions Facial 1 DRO Velvet Hustle 1975 Caballero Home Video
Moral disengagement Diffusion of responsibility can negatively affect personal morals. With diffusion of responsibility, it has been found that people feel less accountable for their work. This lack of accountability can be due to the fact that labour is divided amongst members in a group and so no one member feels an overwhelming amount of responsibility for their organisation or their overall project. It has been found that many members get narrowed into focusing on their individual work, that they eventually forget about any moral aspects. Purely focusing on the functional aspects of their jobs is a result of division of labour, which is a mechanism for diffusion of responsibility.[30] This can be highly concerning for organisations since division of labour is a common practice amongst many. Moral disengagement is likely to be particularly important in organisations because bureaucratic structures and the division of labour seem to lend themselves to moral disengagement mechanisms such as the diffusion and displacement of responsibility (Bandura, 1986). Euphemistic labelling is also common in organisations, such as when managers refer to layoffs as “rightsizing.” Also, with victims out of sight, globalization makes it easier to ignore or distort the harmful consequences of business actions. Thus, moral disengagement seems highly relevant to understanding unethical behaviour in 21st century organizations.[31]



Risk-taking behaviour The risky-shift effect (see groupshift) is the increased likelihood for a group to support or partake in a risky decision or action. Larger groups permit a wider responsibility diffusion than the groups of two or three. As group size increases, the likelihood also increases that the group contains at least one highly risky and influential member who would be able to win over all the others. This demonstrates how larger group size and the increased riskiness of one person can cause the diffusion of responsibility from all group members to only the decisive, risk-taking member.[32] From the group-processes standpoint, then, the risky-shift effect becomes stronger as the groups grow larger. And it has been proved by various studies that the risky-shift effect is more pronounced the larger the size of the group.[33] In risk-taking literature, diffusion of responsibility occurs when individual members of a group feel less personal responsibility for potential failure in the pursuit of risky options than if acting alone.[34][35] Such risky shift is a stable phenomenon that has been shown in experiments involving group discussion and consensus. For example, a study using risks and payoffs based on monetary gain and loss for problem-solving performance found a greater percentage of shift—hence, increased risk taking in group decision making.[12] Other research suggests that risky shifts can also be attributed to group polarization, majority rules, interpersonal comparisons, informational influence, and familiarisation.[36][37] Like diffusion of responsibility in emergency situations, the larger the size of the group during conditions of discussion and information exchange, the greater the risky shift.[38] Bystander effect Arising from the unfortunate case of Catherine "Kitty" Genovese, the bystander effect is a psychological notion which came to light in 1960s New York, and which seems to cast a predominantly daunting light on human behaviour (Gallo, 2015). It highlights the lessening of the likelihood of a person to take immediate action in a certain situation while part of a group or around other people.[39] In a study, Darley and Latané observed subjects' attempts to help when they heard another subject (a confederate) having a seizure. While some subjects thought that they were the only ones hearing the seizure, other subjects thought that another one or another four "bystanders" (who were also subjects) were hearing the same thing. They found that subjects were less likely to help the greater the number of bystanders, demonstrating the bystander effect.[40][18] The bystander effect[23] is a specific type of diffusion of responsibility—when people's responses to certain situations depend on the presence of others. The bystander effect occurs when multiple individuals are watching a situation unfold but do not intervene (or delay or hesitate to intervene) because they know that someone else could intervene, and they feel less responsibility to do so.[23] This is directly caused by the diffusion of responsibility, as it is shown that individuals are much less likely to intervene in a situation when he or she knows others are watching; thus, the responsibility for helping is spread among the group of bystanders, and each bystander does not feel a strong responsibility to do so, so no one helps.[23] However, it has been shown that people's responses and levels of aid can change depending on the type of situation (emergencies versus non-emergencies) as well Automation bias is the propensity for humans to favor suggestions from automated decision-making systems and to ignore contradictory information made without automation, even if it is correct.[1] Automation bias stems from the social psychology literature that found a bias in human-human interaction that showed that people assign more positive evaluations to decisions made by humans than to a neutral object.[2] The same type of positivity bias has been found for human-automation interaction,[3] where the automated decisions are rated more positively than neutral.[4] This has become a growing problem for decision making as intensive care units, nuclear power plants, and aircraft cockpits have increasingly integrated computerized system monitors and decision aids to mostly factor out possible human error. Errors of automation bias tend to occur when decision-making is dependent on computers or other automated aids and the human is in an observatory role but able to make decisions. Examples of automation bias range from urgent matters like flying a plane on automatic pilot to such mundane matters as the use of spell-checking programs.[5] Contents 1 Disuse and Misuse 2 Errors of commission and omission 3 Factors 3.1 Screen design 3.2 Availability 3.3 Awareness of process 3.4 Team vs. individual 3.5 Training 3.6 Automation failure and "learned carelessness" 3.7 Provision of system confidence information 3.8 External pressures 3.9 Definitional problems 4 Automation-induced complacency 5 Sectors 5.1 Aviation 5.2 Health care 5.3 Military 5.4 Automotive 6 Correcting bias 7 See also 8 References 9 Further reading 10 External links Disuse and Misuse An operator's trust in the system can also lead to different interactions with the system, including system use, misuse, disuse, and abuse.[6][vague] The tendency toward overreliance on automated aids is known as "automation misuse".[6][7] Misuse of automation can be seen when a user fails to properly monitor an automated system, or when the automated system is used when it should not be. This is in contrast to disuse, where the user does not properly utilize the automation either by turning it off or ignoring it. Both misuse and disuse can be problematic, but automation bias is directly related to misuse of the automation through either too much trust in the abilities of the system, or defaulting to using heuristics. Misuse can lead to lack of monitoring of the automated system or blind agreement with an automation suggestion, categorized by two types of errors, errors of omission and errors of commission, respectively.[8][9][6] Automation use and disuse can also influence stages of information processing: information acquisition, information analysis, decision making and action selection, and action implementation


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