The Relationship Between Precipitation, Barometric Pressure, Temperature and Shoplifting
The Relationship Between Precipitation, Barometric Pressure, Temperature and Shoplifting
Can hotter weather have an effect on negative human behaviour? Social psychology has long debating the heat hypothesis, saying that as temperatures rise, so do reports of criminal behaviour. Although scattered evidence suggests that a relationship may exist, it is a prolonged debate in which some research falsifies these claims, and some supports it (Anderson, 2001, p.33). This phenomenon has been observed long before the birth of Psychology as a science. Dating back to the 1500, even Shakespeare commented on such hypothesis: “I pray thee, good Mercuito, let’s retire; The day is hot, the Capulets abroad, And if we meet we shall not ‘scape a brawl, Forn now, these hot days, is the mad blood stirring” (1595).
Generally there are several examinations done to support the claims of the aggression-heat hypothesis. Although a persistence pattern of the findings is written mainly by a particular researcher from the University of Iowa, the results and conclusions of his study yet seem to be reliable and replicable. Indeed, more investigation has to be done on this debate, which brings the experiment in this research to find the heat-aggression hypothesis’ validity. Unlike the high scepticism comments in psychological literature about the correlation of heat and crime, there is not much research done in this area of interest. It follows that researchers need to investigate this subject even further.
A summary of the general topic based on the reviewed articles proposes that there might be a relationship between such variables. Therefore, this paper would attempt to find a correlation between temperature, barometric pressure, and precipitation in relation to the rate of shoplifting – while examining the existing literature in this area. The following articles present a review of the current literature in this area of interest. A clever experiment conducted by Anderson et. al.(1993), at the University of Missouri, Columbia, attempted to explain how heat and crime might be related. From a criminal perspective, the researches relate crime to hostile aggressiveness, and try to manipulate heat temperature and measure differences in dependent variables such as affect, cognition and arousal (p.445). This type one assertion using an experimental research design is a 3 (temperature heat level) X2 (negative affect level) ANOVA factorial. While the temperature and the position of playing the video game are varied by the researchers, the recording on negative affect level were based on self-reports, and arousal was measured as heir heart rate.
Participants were undergraduate students Of Missouri University, of which 48 were male and 59 female; they were then randomly selected into each double-blinded group (p.446).
While the researchers vary room temperature with normal, warm, and hot – participants were forced to engage in a brief Pac Man-type video game (p.450) either inverted or normally. After a 10-minute exposure to the video game, researchers measured their heart rate immediately, following them asking participants of their attitudes about abnormal behaviours. Their hostilities with relation to arousal levels indicated their score on the frustration measurement.
In a holistic view, the results of this study indicate that as the temperature level increased, so did signs of negative affect and arousal. They thus predicted that as temperature increases in particular circumstances such as in frustration settings, people are more likely to show signs of either internal or external criminalist characteristics (p. 456). To generalize, when it becomes hotter, it is expected that people may engage in more extreme behaviours such as assaults, murder, abuse, rape, or even theft and robbery. It seems that this experiment has good internal validity when considering the particular study’s isolation of variables; this includes arousal levels, affect influences, the experiment’s design, randomly assigning participants to an experimental group, and an intelligent method of obtaining measuring the results. As the variables were isolated from each other, participants have been tested for their frustration levels either in a normal temperature room, a warm room, or a hot room, each ranges with 15oF difference (p.451). That is, their measurements were not subjective, and the quantitative data makes the experiment more reliable as it can be replicated in the future. Needless to say, the method in which the researchers were able to influence affect results while varying the temperature definitely has significant and applicable outcomes in everyday life. And most importantly, the experiment was conducted in a double blind method, which decreased the chance of error. It is also important to note that the researchers monitored participants’ heart rate to reassure no cardiac or mood disorders while conducting their experiment, in order to preserve the reliability of their results (p.450).
The experiment conducted by Anderson, et.al. (1993) has some flaws however, especially the external validity area. Among some issues, these include the gender selection; population selection; the researchers’ point of error, and in addition possible personality characteristics that might have influenced the results. First and foremost, the study indicated that their participants were 59 females and 48 males. In order to get an accurate measure of how heat may influence human behaviour negatively, it would be more applicable and generalizable if the ratio of males to females were equal. Similarly, the population of the participants encompassed only undergraduate students. Results then cannot be said to apply to other social classes or status, various age groups, or even ethnicities that may not be found among undergraduate students. Second, the particular experiment’s sample size was small and somewhat too general for the researchers to generalize from their findings. This is especially evident in the results, where their term of error is indicated as 0.2% (p.460). And last, some people may have had a predisposition to either be more or less influenced by the cues offered in the experiment. Whether someone is more prone to react to the stimulation or not may have been a characteristic of Type A personality which, according to the procedure, were not investigated prior to the experiment. Given the weaknesses, future experiments of a similar kind may consider an equal ratio of males to females, a personality test, and a more varied method of choosing participants within various social classes, genders, ages, and ethnicities.
In summary of this experiment, their results may generalize to everyday life even though it has a few flaws in it. Aside from gender, class, or ethnicity, their results have indeed yielded significant influenced of heat over negative human behaviour, while other variables may have influence over the results as well; “variables such as biological, psychological, or other environmental factors may have had an effect on the obtained data” (p. 457). Therefore, future experiments of this kind are necessary. Another clever correlational research on hot temperatures and aggressive behaviour such as violent and nonviolent crime was conducted by Anderson (1987). The study hypothesizes that hot temperatures may be related to an increase in aggressive behaviour, also referred to as the temperature-aggression hypothesis (p.1165). The research uses an assertion of type 2 throughout.
The first study was of a longitudinal kind, taking place in the United States between the years 1971 and 1980. It examined crime in terms of business quarters, and its relationship to heat. The second study investigates crime and its association with hotter and cooler cities and additional variables such as age and ethnicity. Violent crimes were considered offences such as murder, rape and assault; non-aggressive crimes included robbery, burglary, larceny-theft and motor vehicle theft (p.1161). Both study one and two display significant evidence for the relationship between hot temperatures and aggressive behaviour.
In the first study, the researcher collected data from the Federal Bureau of Investigation’s Uniform Reports for the United States and the Climatological Data, U.S Department of Commerce (p.1162). Over a ten year span, from 1971 to 1980, crime reports were analyzed and divided into an index displaying crime rates in terms of business quarters. The quarters in which the temperature-aggression hypothesis applied to were the second and third quarters, thus April through September (p.1162). Consequently, this quarter is the hottest season among all four quarters in the United States. The weather data originated from 240 weather stations located throughout the country. In addition, crime and weather data were not only correlated quarterly, but also yearly; thus most crime rates were associated with the hottest seasons, the hottest cities, and the hottest years (p.1163).
The second study conducted by Anderson (1987) collected data from the Federal Bureau of Investigation’s Uniform Reports for the United States, and data from the U.S Department of Commerce such as the Census of the Population: General Population Characteristics. Additional data was retrieved from the Climatological Data, U.S Department of Commerce, such as the “average humidity, number of cloudy days, number of rainy days, number of cold days, heating degree days, and number of snowy days.” Statistics taken from Census of the Population: General Population Characteristics U.S. Department of Commerce and the Census of the Population: General Social and Economic Characteristics U.S. Department of Commerce included: “unemployment, per capita income, poverty rate, mobility, high school education, college education, population size, percentage Black, percentage Spanish, percentage less than 18 years old, percentage 18 to 64 years old, percentage 65 and over, median age, number of law enforcement employees” (p.1166).
For the first study the researcher used an analysis of variance ANOVA statistical method to assess the effects of quarter and year in a 4 (each quarter as a variable) X 10 (robbery, vehicle theft, rape, aggravated assault, burglary, larceny theft, and the similar) design, with one replication per cell” (p.1163). Throughout the second study the researcher correlated crime with population data (p.1166). The research reports significant outcomes as a result; the first study indicated strong correlation between second and third quarters, April through September, and criminal behaviour (p.1166). Similarly, the second study shows a correlation between hotter cities and high aggression rates. However, some of the other variables presented no correlations, such as age and gender.
The study’s examination on the relationship between hot temperatures and crime displays exceptional results and evidence to support the hypothesis. Though with any correlational study, one cannot draw cause and effect conclusions. There may be external influences that could have drastic effects on aggressive behaviour as well. For instance, the researcher states a few possible variables that could affect this study such as: “adults’ vacations, school vacations, hours of daylight, youth unemployment, and free time” (p.1170). Consequently, the researcher promptly states that the interference of such factors is unlikely. It is doubtful that these ‘unlikely’ variables have no effect without further investigation of their effects or relationships. And yet, the extensive amount of data obtained from the trustworthy sources the researchers chose to use indicates a relationship between heat and crime rates.
The external validity of this study seems adequate for the most part, since an exceptional and accurate amount of information was obtained through the United States’ trustworthy sources. Though, it could be challenged by saying that this hypothesis might not adhere to other countries. Thus, the hypothesis of his study may significantly differ in other countries or regions of interest.
There will be no active participants in this study; however, data collected from Shoppers Drug Mart’s inventory, located in the core of Downtown, will be acquired through the store manager.
The data for shoplifting will be obtained from the convenience store Shoppers Drug Mart, located at 586 Granville and Dunsmuir, Vancouver British Columbia, Canada. The data from the store would represent an accurate measure of the amount of missing inventory valued in Canadian dollars. This information will be collected through the researcher, who will acquire consent from their store manager to access such information. The weather inquiries of precipitation and temperature in Vancouver will be collected from The Weather Network’s Channel. In addition, weather information of such source will be retrieved from the Vancouver British Columbia, Canada caption. Weather recordings will be obtained by the researchers daily, and then averaged per week to match the weekly scale for inventory inquiries. The collection of the data will begin on September 25, 2011 and be recorded until November 13, 2011. Averaged weather and inventory theft rates are collected from Sunday through Saturday, and thus recorded weekly. In addition, a written consent form from the store manager will be obtained from the researchers.
The research begins when a consent form is obtained from the store owner. Then, the recorded weather data such as the average weekly temperature and precipitation will be obtained through daily weather reports, from the months of September to November, in the year of 2011. In parallel, the researchers will acquire the monetary value of the collective stolen items within the same week’s time length. Following the recording of this information, theft will be correlated to temperature and then to precipitation. The correlation device that will be used is the Pearson’s correlation coefficient.
Anderson, C.A. (2001). Heat and violence. Current Directions of Psychological Science 10(1), 33-38. doi: 10.1111/1467-8721.00109
Anderson, C. A. (1987). Temperature and aggression: Effects on quarterly, yearly, and city rates of violent and nonviolent crime. Journal of Personality and Social Psychology, 52(6), 1161-1173. doi:10.1037/0022-35188.8.131.521
Anderson, C. A., Deuser, W. E., & DeNeve, K. M. (1995). Hot temperatures, hostile affect, hostile cognition, and arousal: tests of general model of affective aggression. Society for Personality and Social Psychology 21(5), 434-448. Retrieved on Sep. 26, 2011 from: http://www.psychology.iastate.edu/faculty/caa/abstracts/1995-1999/95ADD.pdf
Shakespeare, W., 1595, Romeo and Juliet, Act 3 Scene 1.
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