AASK - Aircraft accident statistics and knowledge: A database of human experience in evacuation, derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However such models have a heavy dependency on real evacuation data in order to (a) identify the key processes and factors associated with evacuation, (b) quantify variables and parameters associated with the identified factors/processes and finally (c) validate the models. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise from three major data sources in order to address these issues. This paper describes the extraction and application of data from one of these sources - aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (aircraft accident statistics and knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK comprises four component sub-databases. These consist of the ACCIDENT (crash details), FLIGHT ATTENDANT (observations and actions of the flight attendants), FATALS (details concerning passenger fatalities) and PAX (observations and accounts from individual passengers) databases. AASK currently contains information from 25 survivable aviation accidents covering the period 4 April 1977 to 6 August 1995, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. In addition to aiding the development of aircraft evacuation models, AASK is also being used to challenge some of the myths which proliferate in the aviation safety industry such as, passenger exit selection during evacuation, nature and frequency of seat jumping, speed of passenger response and group dynamics. AASK can also be used to aid in the development of a more comprehensive approach to conducting post accident interviews, and will eventually be used to store the data directly.

An aircraft accident database of human experience in evacuation derived from aviation accident reports

Computer based mathematical models describing the aircraft evacuation process have a vital role to play in aviation safety. However, such models have a heavy dependency on real evacuation data. The Fire Safety Engineering Group of the University of Greenwich is undertaking a large data extraction exercise in order to address this issue. This paper describes the extraction and application of data from aviation accident reports. To aid in the storage and analysis of the raw data, a computer database known as AASK (Aircraft Accident Statistics and Knowledge) is under development. AASK is being developed to store human observational and anecdotal data contained in accident reports and interview transcripts. AASK currently contains information from 25 survivable aviation accidents covering the period 04/04/77 to 06/08/95, involving some 2415 passengers, 2210 survivors, 205 fatalities and accounts from 669 people. Copyright © 1999 John Wiley & Sons, Ltd.

Ambitious mothers – successful daughters: Mothers’ early expectations for children’s education and children’s earnings and sense of control in adult life

Background. Mothers' expectations for their children's educational attainment are related to children's educational and occupational attainment. Studies have yet to establish, however, the long-term links between maternal expectations and offspring earnings, which are not always related to occupational attainment especially in women, or between maternal expectations and offspring sense of control and self-efficacy, which are pivotal factors in career choice and development. Aims. To explore the role of mothers' expectations for their children's educational attainment in children's earnings attainment and sense of control later in life. Method. Data from sweeps of the 1970 British Cohort Study (BCS70) were used. The study sample was those cohort members with complete information on all the variables of interest. The study sample (N = 3,285) was more educated and less disadvantaged than the whole sample. If cohort members of this type are more likely to have a mother who has high expectations, then our results are biased downwards, which suggests that we underestimate the effect of expectations on our two outcome variables. Results. Mothers' expectations at the age of 10 were positively related to daughters' sense of control at the age of 30 even after controlling for ethnicity, educational attainment, and concurrent partner, parent, and labour market participation status, as well as the following confounding variables (measured at the ages of 0–10): general ability and general ability squared, locus of control, emotional and behavioural problems and emotional and behavioural problems squared, socio-economic disadvantage, parental social class, parental family structure, and mothers' education, child-rearing attitudes, and mental health. Mothers' expectations had no effect on sons' adult outcomes. Conclusions. Given that women are particularly at risk for poor psychological and economic outcomes in adulthood, and that this study likely underestimated the effect of expectations on these two outcomes, this is an important conclusion.