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Compliance of Ultra-Orthodox and secular pedestrians with traffic lights in Ultra-Orthodox and secular locations
Accident Analysis and Prevention 40 (2008) 1919–1924
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Compliance of Ultra-Orthodox and secular pedestrians with traffic lights in Ultra-Orthodox and secular locations Tova Rosenbloom ∗ , Amit Shahar, Amotz Perlman The Phoenix Road Safety Studies, The Interdisciplinary Department of Social Sciences, Bar Ilan University, Ramat Gan 52900, Israel
a r t i c l e
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Article history: Received 21 February 2008 Received in revised form 22 July 2008 Accepted 8 August 2008 Keywords: Traffic lights Crosswalks Red light Gender
a b s t r a c t Following a previous study that revealed the disobedience of Ultra-Orthodox citizens, as compared to secular citizens, of traffic lights at crosswalks, the present study examined the road habits of 995 UltraOrthodox and secular pedestrians in neighboring Ultra-Orthodox and secular cities. Using an observation grid designed specially for this study, the pedestrians were observed at two crosswalks – one in an UltraOrthodox city and one in a secular city – as far as similar traffic parameters, using a logistic regression. The tendency to cross on a red light was assessed as a function of estimated age, gender, religiosity, location (religious/secular), the duration of the red light, the number of vehicles crossing and the number of pedestrians waiting at the curb. Ultra-Orthodox pedestrians committed more violations than secular pedestrians did, and there were more road violations in the Ultra-Orthodox location than there were in the secular location. Fewer traffic violations were committed by “local” pedestrians (Ultra-Orthodox pedestrians in the Ultra-Orthodox location and secular pedestrians in the secular location) than by “foreigners” (Ultra-Orthodox pedestrians in the secular location and secular pedestrians in the Ultra-Orthodox location). The odds of crossing on a red light decreased as a function of both the number of people waiting at the curb and the number of vehicles. Consistent with previous research, males crossed on red much more than females did, regardless of religiosity and location. Our discussion focuses on theoretical and practical explanations of the findings. © 2008 Elsevier Ltd. All rights reserved.
1. Introduction 1.1. Norms of law abidance Pedestrian safety is a major concern in Israel, as it is in other urban settings. In fact, this concern is particularly severe in Israel: thirty-three percent of road accident fatalities in Israel are pedestrians (National Autority of Road Safety, 2006). According to a report by the Israeli Traffic Police (Traffic Police, 2006), most of the fatalities among pedestrians are caused by pedestrians’ violations of traffic laws. Levels of commitment to law abidance have been discussed in previous research (Gibson and Caldeira, 1996). Generally, law abidance depends on a variety of factors, such as the extent to which the law is perceived as just and reasonable on the one hand, and the benefits that can be achieved through breaking the law, the odds of being caught by the authorities and the severity of the penalty on the other hand (Tyler, 2006). There is evidence to suggest that specific social groups have different approaches to
∗ Corresponding author. Tel.: +972 3 5741011; fax: +972 3 5741959. E-mail address: [email protected] (T. Rosenbloom). 0001-4575/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.aap.2008.08.004
law abidance due to circumstances of conflict (Torgler, 2006). The present study examined the behavioral expressions of law abidance among Ultra-Orthodox citizens as compared to secular citizens in Israel. 1.2. Religiosity and law abidance Religious motivation can affect behavioral norms and attitudes even if it is not formally stipulated (Hardin, 1997). Margolis (1997) explored the relationship between morality and religiosity. Religiosity includes attitudes towards behavior regarded as “right.” Thus, “right” behavior from a religious point of view refers to proper conduct in a sense that diverges from the secular sense of what is (from a secular perspective) fair and just. As a sanctioning system that legitimizes and reinforces social values, religiosity might inhibit illegal activity. Hull (2000) showed that countries with higher rates of religious membership have significantly less violent and non-violent crime. Among the Orthodox, religious laws have the highest priority. When various values conflict, Orthodox respondents express a stronger belief in the supremacy of religious laws over state laws than other citizens do; they perceive religious laws as more compelling than state laws (Yagil and Ratner, 2002).
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1.3. Religiosity and traffic law abidance One of the most available contexts in which citizens are confronted with legal demands in everyday life is that of traffic regulations. Rosenbloom et al. (2004) found that age and gender differences notwithstanding, pedestrians in an Ultra-Orthodox environment committed about three times as many traffic violations as pedestrians in a secular environment did. A robust age effect has been found in relation to traffic violations (Diaz, 2002; Jonah, 1997; Rosenbloom and Wolf, 2002). There is evidence that the older the road user, the fewer violations committed (Holland and Hill, 2007). Nonetheless, the rate of law abidance among Ultra-Orthodox pedestrians is so low that the age-related correlation is not perceptible in this population: age had an effect on violation rates among secular pedestrians but not among UltraOrthodox pedestrians. The findings of Rosenbloom et al. (2004), which focused on the road behavior of pedestrians in their home neighborhood, raised the question of group influence on individuals as far as safe road crossing. The impact of others’ behavior on the individual has been investigated and has been found to be complex (Bamberg et al., 2007). The current research focuses on the dynamics of the behavior of pedestrians of two social groups (secular and Ultra-Orthodox) in both secular and Ultra-Orthodox environments. It examines the road behavior of (apparently) Ultra-Orthodox residents when they are not in their own neighborhoods. Do these pedestrians adjust their road habits to fit those prevalent in the secular city or do they stick to the same behavior engaged in at home? And as to the secular residents who incidentally pass through the neighboring Ultra-Orthodox city—do they display the same disregard for traffic rules shown by local residents, or do they behave as they would in their own city? 1.4. Familiarity and law abidance The extent to which road users are familiar with their surroundings may play a crucial role in their road behavior (Blatt and Furman, 1998). Familiarity can increase safe road behavior as a consequence of pedestrians’ awareness of specific traffic hazards. But, at the same time, road familiarity can lead to overconfident behavior and to an illusionary feeling of control. Hamed (2001) observed pedestrians who live in the vicinity of a particular intersection (and hence are more familiar with it). He found that people in a familiar setting were more reluctant to adhere to strict rules. Consistent with this finding, Rosenbloom et al. (2007) showed that in familiar locations, road users performed more traffic violations and exhibited more dangerous behavior than those in non-familiar areas. 1.5. Research rationale Building on the factors discussed thus far, the present study sought to examine pedestrians’ behavior – specifically, crossing on a red light – in their natural environment (secular pedestrians in a secular city and Ultra-Orthodox pedestrians in an Ultra-Orthodox city) and in a foreign environment (secular pedestrians in an UltraOrthodox city and Ultra-Orthodox pedestrians in a secular city). Based on previous findings (Rosenbloom et al., 2004) we predicted that Ultra-Orthodox pedestrians (described above) would cross the street on red lights more often than secular pedestrians would, and that pedestrians in the Ultra-Orthodox location would cross on red lights more often than pedestrians in the secular area would. We also expected that the dominant behavioral pattern in each location would affect the road behavior of non-local pedestrians. Additionally, based on the fact that higher average traffic volumes at intersections are associated with more pedestrian crashes
(Lee and Abdel-Aty, 2005) and that both vehicle and pedestrian volumes are positively associated with pedestrians’ tendency to cross on red lights (Rosenbloom, under review), it was expected that these parameters would affect pedestrians’ road behavior as well. 2. Method 2.1. Participants In total, 995 pedestrians were observed, of whom 515 were females (51.8%) and 480 were males (48.2%). Of the participants, about 8% (85) were children, 9% (90) were teenagers, 40% (420) were within the age group of 20–60 and the rest – about 43% (400) – were above the age of 60. In the Ultra-Orthodox city, 461 pedestrian were observed, of whom 384 were Ultra-Orthodox and 77 were secular. In the secular city, 534 pedestrian were observed, of whom 433 were secular and 101 were Ultra-Orthodox. Ultra-Orthodox people are wearing very typical dressing in near to 100% of the cases: Men are dressed with white shirts, black suits even in the hottest days of the Israeli summer and of course with one of some kind of hat on their head. Mostly, Ultra-Orthodox males have beard. Women wear long sleeve shirts, long skirts, socks and a hat or a wig on their head (Ribner, 2003). In an inter-observer validation procedure we trained the observers to define the UltraOrthodox pedestrians. 2.2. Instruments—the observation grid An observation grid, designed specially for this study (founded on the grid described in Rosenbloom et al., 2004), was planned to register the behavioral parameters of the pedestrians participating in the study. The data included variables such as estimated age, gender, religiosity, location (religious/secular), the duration of the red light, the number of vehicles crossing and the number of pedestrians waiting at the curb. Two dependent variables were registered for each participant: her decision whether or not to cross on a red light and the duration of her wait at the curb before crossing. 2.3. Location The observations were conducted in two cities, similar in population size, in the center of Israel (Bnei Brak and Petach Tikva). The crosswalks chosen for observation were both in urban settings; both were lighted pedestrian crossings on undivided streets. One crosswalk (in the Ultra-Orthodox city) was eight meters wide, the other (in the secular city) nine meters wide. Both were on twolane one-way streets. In both locations the duration of red lights was 52–53 s on average. The vehicle volume was 456 vehicles per hour and the pedestrian volume was 166 pedestrians per hour. The average number of vehicles crossing the intersections while the pedestrian light was red was 11.4 (S.D. = 4.06, min = 1, max = 22). These statistics were similar in both locations. The locations, the times of day suitable for conducting the study and the observation grid were tested in a pilot study. The two locations were chosen after many trials aimed at finding suitable crosswalks with optimal volumes of vehicles and pedestrians which was within the limits of an accurately and reliably observed. Data provided by the Police Traffic Department indicated that both locations had similar traffic volumes. This related to the same period of the day, time of year, weather conditions as that of the data collection, at either or both locations. None of these occasions of observations was related to special events. In both cities the crosswalks chosen were centrally located on routes that serve shopping venues, medical services, schools, etc.
T. Rosenbloom et al. / Accident Analysis and Prevention 40 (2008) 1919–1924 Table 1 A summary of the prediction results
Actual waited Actual crossed Overall percentage
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groups of 8, 72 in groups of 9, 50 in groups of 10, 33 in groups of 11 and 24 in groups of 12.
Predicted waited
Predicted crossed
Percentage correct
778 181
19 17
97.6 8.6 79.8
3. Results
No exceptional demographic features such as age, occupation or socio-economic status had any dominance at these locations. (This is of course important for our confidence level in the generalization power of the results.) 2.4. Procedure The study was carried out in eight sessions of one hour each, from 12:00 to 13:00 P.M. on the same days of the week. The weather was warm and pleasant during all sessions. Five trained observers stood by the side of the road and unobtrusively collected data about the pedestrians’ crossing behavior on red lights. These observers employed the following arrangement: one was responsible for observing children and young pedestrians, the second for observing adult pedestrians, the third for observing elderly pedestrians; the forth and the fifth observers were responsible for tracking the total number of pedestrians crossing the road and the total number of vehicles passing by, respectively. At the end of each session, the total numbers of the pedestrians recorded by first, second and third observers, was compared to the total number of pedestrians recorded by the forth observers. All in all, these comparisons were close to perfect. This procedure has been conducted in order to minimize the possibility that on of the pedestrians would be recorded twice by two different age-group-recording observers or omitted altogether. The observers were carefully trained to carry out the study properly: they were instructed on standardizing their criteria for classifying participants as “red light crossers” or “green light crossers” (red light crossers were those who started to cross when the light was already red) and for measuring the length of pedestrians’ waits before crossing. In an inter-observer process they were trained to record the pedestrians by the definition of “group” as people who are waiting to cross at the same time since the light has been changed to red. They were also trained to estimate the age group of the participants and to classify them as belonging to one of the four groups used: under 20 (children and teenagers), 20–60 and over 60. The training included 10 trials during which the observers estimated the ages of people from each age category and later compared their estimations with the subjects’ real ages. The average pedestrian group size was 5.84 (S.D. = 2.59). Eighteen pedestrians waited alone, 69 in pairs, 114 in trios, 132 in groups of 4, 145 in groups of 5, 144 in groups of 6, 146 in groups of 7, 48 in
Of the 995 pedestrians observed in this study (overall, in both sites), 198 (19.9%) crossed on red lights. Of these 198, 91 (45.9%) were secular and 107 (54.1%) were Ultra-Orthodox (chisquare = 2.77, d.f. = 1, p > 0.1), 81 (40.9%) were observed in the secular city and 117 (59.1%) in the Ultra-Orthodox city (chisquare = 16.18, d.f. = 1, p < 0.001). The main interest of this study, in line with previews research, is the influence of age, gender, religiosity, location and number of pedestrians waiting to cross on tendency to cross on a red light. Number of vehicles at the intersection and duration of the red light was also introduced as control but as we are also interested in these variables, as they have implications for decision making processes. And finely, we introduced in to the analyses the interaction of religiosity and location in line with the introduction. A binary logistic regression analysis (using SPSS) was performed with Tendency to cross on a red light as the dependent variable and Age (children and teenagers vs. adults and elderly), Gender, Religiosity, Location, Number of pedestrians waiting to cross, Number of vehicles at the intersection, Duration of the red light (24–64 min vs. 70 min) and the interaction between Religiosity and Location as predictor variables. A total of 995 cases were analyzed and the full model significantly predicted the tendency to cross on a red light (omnibus chi-square = 108.65, d.f. = 8, p < 0.001). The model accounted for between 10.4 (Cox & Snell R Square) and 16.4 (Nagelkerke R Square) of the variance in tendency to cross on a red light, with 97.6% of the pedestrians who waited for a green light successfully predicted; however, only 8.6% of the predictions for the pedestrians who did not wait were accurate (see Table 1). Overall 79.9% of the predictions were accurate. Table 2 presents the coefficients, the Wald statistic and the associated degrees of freedom and probability values for each of the predictor variables. It shows that Gender, Number of pedestrians waiting to cross, Number of vehicles at the intersection and the interaction of Religiosity and Location reliably predicted tendency to cross on a red light. The values of the coefficients reveal that an increase of one pedestrian in the waiting group is associated with a decrease in the odds of crossing on a red light by a factor of 0.73 (as noted in Section 4), and that an increase of one vehicle is associated with a decrease in the odds of crossing on a red light by a factor of 0.95. In addition, males were more likely to cross on red lights than females. As can be seen in Table 3 we did not find statistically significant evidence that Ultra-Orthodox pedestrians tend to cross the street on red lights more often than secular pedestrians do, or vice versa (the results were 22% Ultra-Orthodox vs. 17% secular pedestrians who crossed on red). We did find, however, an
Table 2 The coefficients for each predictor variable, the Wald statistic and the associated significant values
Age Gender Religiosity Location Number of pedestrians waiting to cross Number of vehicles at the intersection Duration of the red light Religiosity by Location Constant
B
S.E.
Wald
d.f.
Sig.
Exp(B)
−0.297 0.437 0.384 0.376 −0.305 −0.045 0.345 −1.046 0.410
0.236 0.172 0.289 0.323 0.047 0.022 0.189 0.403 0.414
1.585 6.483 1.758 1.357 43.134 4.229 3.328 6.734 0.979
1 1 1 1 1 1 1 1 1
0.208 0.011 0.185 0.244 0.000 0.040 0.068 0.009 0.322
0.743 1.548 1.468 1.456 0.737 0.956 1.411 0.352 1.506
The relative effects of these factors may be summarized by the logistic regression equation: Log odds = 0.410 − 0.297 Age + 0.437 Gender + 0.384 Religiosity + 0.376 Location − 0.305 Number of pedestrians waiting to cross − 0.045 Number of vehicles at the intersection + 0.345 Duration of the red light + 1.046 Religiosity by Location.
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Table 3 Absolute numbers of crossing and not crossing (cross/not cross ratios), for UltraOrthodox city and Secular city, and for the Ultra-Orthodox and Secular Levels of variables
Count cross/not cross
Ultra-Orthodox Secular Ultra-Orthodox city Secular city
107/378 91/419 117/344 81/453
Ultra-Orthodox city Ultra-Orthodox Secular
83/301 34/43
Secular city Ultra-Orthodox Secular
24/77 57/376
Ultra-Orthodox Ultra-Orthodox city Secular city
83/301 24/77
Secular Ultra-Orthodox city Secular city
34/43 57/376
and strong gender roles. Their socio-economic status is below the Israeli average due to low income (most men engage only in daily prayer and the study of religious texts) and large families (Ribner, 2003). It appears that to the Ultra-Orthodox Jewish population, state rules (like traffic rules) are perceived as inferior to the Jewish Halacha rules (Rosenbloom et al., 2004). 4.1. The religiosity–location interaction
interaction between Religiosity and Location. Specifically, in the Ultra-Orthodox city, 44% of the secular pedestrians, but only 21% of the Ultra-Orthodox pedestrians, crossed on a red light (chisquare = 17.20, d.f. = 1, p < 0.001). This pattern was reversed in the secular city, where 23% of the Ultra-Orthodox pedestrians, but only 13% of the secular pedestrians, crossed on red (chi-square = 7.14, d.f. = 1, p < 0.05). We also discovered that males tend to cross on red more often than females do (24% males vs. 15% females). In addition, increases in the number of pedestrians waiting to cross and increases in the number of vehicles at the intersection are both associated with a decrease in the odds of crossing on a red light. 4. Discussion This study aimed to investigate the comparative abidance of Ultra-Orthodox and secular pedestrians with traffic rules. In his Theory of Moral Sentiments, Smith (1976) analyzed religiosity from a rational point of view and noted that religiosity acts as a kind of internal moral enforcement mechanism. Mears et al. (2006) assert that religiosity may affect criminogenic factors, such as drug use. Changes in these factors may ultimately improve recidivism and behavioral outcomes among participants. Smith (2003) identified three dimensions in religiosity that may affect delinquent behavior, each of which includes three factors: (1) moral order (moral directives, spiritual experiences and role models); (2) learned competencies (community and leadership skills, coping skills and cultural capital); and (3) social and organizational ties (social capital, network closure and extra-community skills). In each case, Smith’s proposed logic is that religion reduces delinquency. The Ultra-Orthodox community observed in this research is typified by the traits described by Smith (2003), as it is an extremely religious group that endorses patterns of voluntary segregation. This Jewish community is governed by scrupulous observance of Jewish law, aimed at moving closer to God. Any deviation from divinely ordained biblical requirements is unacceptable; the community emphasizes stricter rather than more lenient legal interpretations, and these results in higher levels of spirituality. This ideology is reflected in the manner of the community members: Ultra-Orthodox people typically dress modestly and rather uniformly (particularly males). They espouse values of marriage and large families (five to ten children per family is quite common) as fundamental and preserve gender-segregated education
Our principle research question was whether the road-crossing behavior of Ultra-Orthodox pedestrians is different from that of secular pedestrians and whether such behavior depends on the environment in which it occurs. All in all, there is some evidence, though no significant evidence for it that Ultra-Orthodox pedestrians tend to commit more road violations than secular pedestrians do; at the same time, more road violations were registered in the Ultra-Orthodox location than were registered in the secular location. The most interesting finding of this research, however, is the significant interaction between Religiosity and Location. The tendency to cross on a red light was dependent on the environment. In regard to pedestrians’ traffic violations, this means that in the Ultra-Orthodox city as well in the secular city, pedestrians in an environment markedly different from their own committed approximately twice as many traffic violations as locals did. People – Ultra-Orthodox as well as secular – may feel discomfort about breaking social norms perceived as such in certain environments. Grasmick et al. (1991) argue that there are agents other than the state that can threaten violators. They argue that agents in one’s near surroundings reduce the expected utility of crime through informal and “interpersonal sanctions” (e.g., diminished respect). They state: “While embarrassment’s most immediate consequence probably is physiological discomfort, more long-term consequences include loss of valued relationships, and perhaps restricted opportunities to achieve other valued goals (p. 253).” Grasmick et al. mention feelings of shame or guilt as another factor that can reduce the violation of social norms. These sentiments may influence behavior, reducing the perceived benefits of rule violation. According to Lewis (1971), guilt arises when individuals realize that they have acted irresponsibly or in violation of a rule or social norm that they have internalized. To sum this point up, it might be that both secular and Ultra-Orthodox pedestrians feel much more comfortable about breaking traffic rules when they are not in their own neighborhoods. However, based on Rosenbloom et al. (2004) we assume that the negative safety climate in Ultra-Orthodox environment (caused apparently by the tendency of Ultra-Orthodox residents to break the traffic laws) might be adopted by bypassing strangers. 4.2. Gender A higher rate of males than females crossed the street on a red light. This trend was not influenced by the religiosity of the pedestrians. The over-representation of males vs. females in risky behavior and law-breaking has been well-documented in previous works: men report crossing on a “don’t walk” sign more frequently, and express weaker ‘instrumental’ and ‘normative’ motives for safe crossing (Yagil, 2000). Additionally, males are more risky than females both as drivers and as pedestrians and are involved in more fatal accidents (Harre et al., 1996). This finding is stable in all age groups: more boys than girls are injured on the roads, and this trend remain stable through old age (Connelly et al., 1998).
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4.3. Vehicle volume Lee and Abdel-Aty (2005) indicated that car crashes involving pedestrians are more likely to occur at intersections with higher traffic volume, which increases the potential conflicts between pedestrians and vehicles. However, it appears that the rate of increase in accidents gradually diminishes as average annual daily traffic increases. This trend is consistent with prior European models, which showed that the number of crashes involving pedestrians is approximately proportional to the square root of vehicle volume. However, the rate of increase is steeper at lower average traffic values. In the present study, an increase in the number of vehicles was found to be associated with a decrease in the odds of crossing on a red light. Although pedestrians are supposed to rely solely on traffic lights to determine whether or not to cross a lighted intersection, a judgment of how dangerous it might be to cross on red is clearly involved, though not necessarily consciously. Normally, people are more inclined to cross on a red light when they see the situation as less dangerous. Yagil (2000) found gender differences with regard to the perception of situational factors as dangerous: whereas among women, safe road crossing is perceived as predicted by the presence and behavior of other pedestrians, among men it is perceived as influenced by the traffic volume and other conditions. In other words, women are more influenced by their social environment, whereas men seem to be more concerned with the physical aspects of the setting. The current study, however, did not find any gender differences with regard to the relationship between traffic light abidance and the volume of pedestrians or traffic.
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Miller and Byrnes, 1997) who emphasize adolescents’ tendency to take more risks in the presence of peer groups. The pragmatic explanation for the higher rate of people to cross on red when waiting at the curb alone is that people are aware, from past experience, that the larger the group waiting at the curbside, the shorter the amount of time they can expect to wait until the light turns green. A quick cost-benefit calculation suggests that they invest a few more seconds in waiting so as to be on the safe side. This would suggest that it might be beneficial for traffic lights to display the amount of time that remains until the light is to turn green. From another pragmatic point of view, large groups of pedestrians crossing together on red may feel safer than individuals do because of the “safety in numbers” effect that may occur when many pedestrians cross simultaneously. Additionally, pedestrians may assume that oncoming traffic is better able to see them and more likely to come to a stop when there are many people huddled at the crosswalk, and this may encourage more crossing as well. Consequently, greater trust may be placed in drivers under these conditions, reducing the perceived need for caution by pedestrians. The most interesting finding of this research is that in both locations, “foreigners” committed more traffic violations than “natives” did. Additional findings were that the larger the group of the people waiting on the curbside, the lower the rate of people crossing on a red light; and that an increase in vehicle volume was associated with a decrease in the odds of crossing on a red light. Consistently with previous research, males crossed on red much more often than females did, regardless of religiosity and location. 4.5. Methodological remarks
4.4. Pedestrian volume The current study found that the larger the group of people waiting at the curb, the lower the rate of people to cross on a red light. A few reasonable explanations elucidate this pattern; one is theoretical, the others pragmatic. Hirschi’s Social Control Theory (Hirschi, 1969) suggests that the mechanism behind obedient behavior is people’s motivation to be rewarded simply for conformism. Normal individuals have buffers that prevent them from breaking the law and therefore encourage them to behave in a normative way. The sanctions administered by society are much more of a deterrent for normative people than formal sanctions are (Hirschi and Gottfredson, 1994). Thus, people who arrive at a crosswalk alone on a red light are not concerned about social criticism and are therefore more likely to break the law; while those surrounded by other pedestrians feel much more committed to the social order and to social norms. If this is true, this tendency might have potential beneficial implications. Hirschi (2004) assumes that the strengthening of individuals’ bonds to conventional institutions of society might increase their commitment to normative behavior. Authorities should therefore employ this principle in order to increase self-control and with it normative, safe behavior. This pattern has exceptions. A comprehensive project (BenMoshe, unpublished thesis work) that examined the road-crossing decisions of young children and adolescents (6-, 9- and 13-year-old boys and girls) revealed a converse trend: each participant standing at a crosswalk with his or her peer group was much more willing to take risks while crossing than the same participant was while crossing alone. Thus, the mechanism of social facilitation (Corston and Colman, 1996; Sanna and Shotland, 1990) works differently when children (pre-adolescents) are involved. Support for this notion is supplied by researchers (Christenson and Morrongiello, 1997;
Field settings, such as that used in the present study, have obvious advantages, but certain limitations as well. The conditions in a natural setting constrain the ability of the observers to measure some relevant behavioral parameters, such as the exact waiting time at the curb, problematic operational definitions, pertinence to age and culture groups’ estimations, and uncertainty of the control for traffic volume. Another interesting piece of information lost in the present study is the probable interaction between foreign and local citizens waiting for the light to change: Who is the first to cross the street on red and what is the reaction of the others? Special equipment could solve such problems in further research. Beyond such technical problems, one must take into consideration that the theoretical explanations offered to the Ultra-Orthodox pedestrians’ relatively unsafe road behavior can stem from their cultural conventions rather than from their religiosity; though the two are hard to differentiate. Larger families living in worse financial conditions may pay less attention to rules (Park, 2007), including traffic rules. 4.6. Practical implications The unique dynamics of the mixed group on the curb (UltraOrthodox and secular pedestrians) may reflect the tendency of people to absorb the cultural (safety) climate of their environment (Guldenmund, 2000). As mentioned above, religious laws are perceived by religious people as more compelling than state laws (Yagil and Ratner, 2002), and this may be why Ultra-Orthodox pedestrians flout traffic rules more often than secular people do; yet strangers who happen to arrive in an Ultra-Orthodox neighborhood may modify their behavior so as to “fit in” with the locals. This trend must be taken into consideration in the planning of educational campaigns aimed at changing road behavior.
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The Ultra-Orthodox community is heavily influenced by its leadership (Rabbis). For example, Timor (1996) found that ex-prisoners learning in Israeli “yeshivas for repentants” (religious training institutions) benefit from a rehabilitation program which enables them to integrate as equals into the community and thus to reconstruct their social- and self-images, without being threatened by their criminal past. Thus it is clear that the Rabbis must play a key role in programs aimed at improving traffic behavior in the UltraOrthodox community if these programs are to be effective. The leaders of the Ultra-Orthodox community should consider not only the Ultra-Orthodox population but also the secular pedestrians around them. As regards both populations, increased compliance with traffic rules would fit a very important value of the Ultra-Orthodox Jewish people—the sanctity of life, given to people by God (“Pikuach Nefesh”). Rabbis should take this factor into account in emphasizing the importance of abiding by state laws as well as Halacha laws. References Bamberg, S., Hunecke, M., Blobaum, A., 2007. Social context, personal norms and the use of public transportation: two field studies. Journal of Environmental Psychology 27, 190–203. Blatt, J., Furman, S.M., 1998. Residence location of drivers involved in fatal crashes. Accident Analysis and Prevention 30, 705–711. Christenson, S., Morrongiello, B.A., 1997. The influence of peers on children’s judgments about engaging in behaviors that threaten their safety. Journal of Applied Developmental Psychology 18, 547–562. Connelly, L.M., Conaglen, H.M., Parsonson, B.S., Isler, R.B., 1998. Child pedestrians’ crossing gap thresholds. Accident Analysis and Prevention 30, 443–453. Corston, R., Colman, A.M., 1996. Gender and social facilitation effects on computer competence and attitudes toward computers. Journal of Educational Computing Research 14, 171–183. Diaz, E.M., 2002. Theory of planned behavior and pedestrians’ intentions to violate traffic regulations. Transport Research Part F: Traffic, Psychology and Behavior 5, 169–175. Gibson, J.L., Caldeira, G.A., 1996. The legal cultures of Europe. Law and Society Review 3, 55–85. Guldenmund, F.W., 2000. The nature of safety culture: a review of theory and research. Safety Science 34, 215–257. Grasmick, H.G., Bursik, R.J., Cochran, J.K., 1991. Render unto Caesar what is Caesar’s”: religiosity and taxpayers’ inclinations to cheat. Sociological Quarterly 32, 251–266. Hamed, M., 2001. Analysis of pedestrians’ behavior at pedestrian crossings. Safety Science 38, 63–82. Hardin, R., 1997. The economics of religious belief. Journal of Institutional and Theoretical Economics 153, 259–278. Holland, C., Hill, R., 2007. The effect of age, gender and driver status on pedestrians’ intentions to cross the road in risky situations. Accident Analysis and Prevention 39, 224–237.
Hull, B.B., 2000. Religion still matters. Journal of Economics 26, 35–48. Harre, N., Field, J., Kirkwood, B., 1996. Gender differences and areas of common concern in the driving behaviors and attitudes of young adolescents. Journal of Safety Research 273, 163–173. Hirschi, T., 1969. Causes of Delinquency. University of California, Berkley. Hirschi, T., Gottfredson, M.R. (Eds.), 1994. The Generality of Deviance. Transaction, New Brunswick. Hirschi, T., 2004. Self-control and crime. In: Baumeister, R.F., Vohs, K.D. (Eds.), Handbook of Self-Regulation: Research, Theory and Applications. Guilford Press, New York, NY, pp. 537–552. Jonah, B.A., 1997. Sensation seeking and risky driving: a review and synthesis of the literature. Accidental Analysis and Prevention 5, 651–665. Lee, C., Abdel-Aty, M., 2005. Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida. Accident Analysis and Prevention 37, 775–786. Lewis, H.B., 1971. Shame and Guilt in Neurosis. International University Press, New York. Margolis, H., 1997. Religion as paradigm. Journal of Institutional and Theoretical Economics 153, 242–252. Mears, P.D., Roman, C.G., Wolff, A., Buck, J., 2006. Faith-based efforts to improve prisoner reentry: assessing the logic and evidence. Journal of Criminal Justice 34, 351–367. Miller, D.C., Byrnes, J.P., 1997. The role of contextual factors and personal factors in children’s risk taking. Developmental Psychology 33, 814–823. National Autority of Road Safety, 2006. Annual report. Park, Y., 2007. The relationship between suburbanization and crime in United States metropolitan areas. Dissertation Abstracts International Section A: Humanities and Social Sciences 68, 1171. Ribner, D., 2003. Modifying sensate focus for use with Haredi (Ultra-Orthodox) Jewish couples. Journal of Sex & Marital Therapy 29, 165–171. Rosenbloom, T., Wolf, Y., 2002. Sensation seeking and detection of risky road signals: a developmental perspective. Accident Analysis and Prevention 34, 569–580. Rosenbloom, T., Nemrodov, D., Barkan, H., 2004. For heavens’ sake follow the rules: pedestrians’ behavior in an ultra-orthodox and a non-orthodox city. Transportation Research Part F 7, 395–404. Rosenbloom, T., Perlman, A., Shahar, A., 2007. Women drivers’ behavior in well-known versus less familiar locations. Journal of Safety Research 38, 283–288. Rosenbloom, T., under review. Road crossing in red light of singles and groups. Sanna, L.J., Shotland, R.L., 1990. Valence of anticipated evaluation and social facilitation. Journal of Experimental Social Psychology 26, 82–92. Smith, A., 1976. Theory of Moral Sentiments. Oxford University Press, Oxford. Smith, C., 2003. Theorizing religious effects among American adolescents. Journal for the Scientific Study of Religion 42, 17–30. Timor, U., 1996. Coping with the criminal past of ex-delinquents undergoing rehabilitation in Yeshivas for repentants. Megamot 38, 30–47. Torgler, B., 2006. The importance of faith: tax morale and religiosity. Journal of Economic Behavior & Organization 16, 81–109. Traffic Police, 2006. Annual report. Tyler, T.R., 2006. Psychological perspective on legitimacy and legitimation. Annual Review of Psychology 57, 375–400. Yagil, D., 2000. Beliefs, motives and situational factors related to pedestrians’ selfreported behavior at signal-controlled crossings. Transportation Research Part F 3, 1–13. Yagil, D., Ratner, A., 2002. Between commandments and laws: religiosity, political ideology, and legal obedience in Israel. Crime Law & Social Change 38, 185–209.
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Compliance of Ultra-Orthodox and secular pedestrians with traffic lights in Ultra-Orthodox and secular locations Tova Rosenbloom ∗ , Amit Shahar, Amotz Perlman The Phoenix Road Safety Studies, The Interdisciplinary Department of Social Sciences, Bar Ilan University, Ramat Gan 52900, Israel
a r t i c l e
i n f o
Article history: Received 21 February 2008 Received in revised form 22 July 2008 Accepted 8 August 2008 Keywords: Traffic lights Crosswalks Red light Gender
a b s t r a c t Following a previous study that revealed the disobedience of Ultra-Orthodox citizens, as compared to secular citizens, of traffic lights at crosswalks, the present study examined the road habits of 995 UltraOrthodox and secular pedestrians in neighboring Ultra-Orthodox and secular cities. Using an observation grid designed specially for this study, the pedestrians were observed at two crosswalks – one in an UltraOrthodox city and one in a secular city – as far as similar traffic parameters, using a logistic regression. The tendency to cross on a red light was assessed as a function of estimated age, gender, religiosity, location (religious/secular), the duration of the red light, the number of vehicles crossing and the number of pedestrians waiting at the curb. Ultra-Orthodox pedestrians committed more violations than secular pedestrians did, and there were more road violations in the Ultra-Orthodox location than there were in the secular location. Fewer traffic violations were committed by “local” pedestrians (Ultra-Orthodox pedestrians in the Ultra-Orthodox location and secular pedestrians in the secular location) than by “foreigners” (Ultra-Orthodox pedestrians in the secular location and secular pedestrians in the Ultra-Orthodox location). The odds of crossing on a red light decreased as a function of both the number of people waiting at the curb and the number of vehicles. Consistent with previous research, males crossed on red much more than females did, regardless of religiosity and location. Our discussion focuses on theoretical and practical explanations of the findings. © 2008 Elsevier Ltd. All rights reserved.
1. Introduction 1.1. Norms of law abidance Pedestrian safety is a major concern in Israel, as it is in other urban settings. In fact, this concern is particularly severe in Israel: thirty-three percent of road accident fatalities in Israel are pedestrians (National Autority of Road Safety, 2006). According to a report by the Israeli Traffic Police (Traffic Police, 2006), most of the fatalities among pedestrians are caused by pedestrians’ violations of traffic laws. Levels of commitment to law abidance have been discussed in previous research (Gibson and Caldeira, 1996). Generally, law abidance depends on a variety of factors, such as the extent to which the law is perceived as just and reasonable on the one hand, and the benefits that can be achieved through breaking the law, the odds of being caught by the authorities and the severity of the penalty on the other hand (Tyler, 2006). There is evidence to suggest that specific social groups have different approaches to
∗ Corresponding author. Tel.: +972 3 5741011; fax: +972 3 5741959. E-mail address: [email protected] (T. Rosenbloom). 0001-4575/$ – see front matter © 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.aap.2008.08.004
law abidance due to circumstances of conflict (Torgler, 2006). The present study examined the behavioral expressions of law abidance among Ultra-Orthodox citizens as compared to secular citizens in Israel. 1.2. Religiosity and law abidance Religious motivation can affect behavioral norms and attitudes even if it is not formally stipulated (Hardin, 1997). Margolis (1997) explored the relationship between morality and religiosity. Religiosity includes attitudes towards behavior regarded as “right.” Thus, “right” behavior from a religious point of view refers to proper conduct in a sense that diverges from the secular sense of what is (from a secular perspective) fair and just. As a sanctioning system that legitimizes and reinforces social values, religiosity might inhibit illegal activity. Hull (2000) showed that countries with higher rates of religious membership have significantly less violent and non-violent crime. Among the Orthodox, religious laws have the highest priority. When various values conflict, Orthodox respondents express a stronger belief in the supremacy of religious laws over state laws than other citizens do; they perceive religious laws as more compelling than state laws (Yagil and Ratner, 2002).
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1.3. Religiosity and traffic law abidance One of the most available contexts in which citizens are confronted with legal demands in everyday life is that of traffic regulations. Rosenbloom et al. (2004) found that age and gender differences notwithstanding, pedestrians in an Ultra-Orthodox environment committed about three times as many traffic violations as pedestrians in a secular environment did. A robust age effect has been found in relation to traffic violations (Diaz, 2002; Jonah, 1997; Rosenbloom and Wolf, 2002). There is evidence that the older the road user, the fewer violations committed (Holland and Hill, 2007). Nonetheless, the rate of law abidance among Ultra-Orthodox pedestrians is so low that the age-related correlation is not perceptible in this population: age had an effect on violation rates among secular pedestrians but not among UltraOrthodox pedestrians. The findings of Rosenbloom et al. (2004), which focused on the road behavior of pedestrians in their home neighborhood, raised the question of group influence on individuals as far as safe road crossing. The impact of others’ behavior on the individual has been investigated and has been found to be complex (Bamberg et al., 2007). The current research focuses on the dynamics of the behavior of pedestrians of two social groups (secular and Ultra-Orthodox) in both secular and Ultra-Orthodox environments. It examines the road behavior of (apparently) Ultra-Orthodox residents when they are not in their own neighborhoods. Do these pedestrians adjust their road habits to fit those prevalent in the secular city or do they stick to the same behavior engaged in at home? And as to the secular residents who incidentally pass through the neighboring Ultra-Orthodox city—do they display the same disregard for traffic rules shown by local residents, or do they behave as they would in their own city? 1.4. Familiarity and law abidance The extent to which road users are familiar with their surroundings may play a crucial role in their road behavior (Blatt and Furman, 1998). Familiarity can increase safe road behavior as a consequence of pedestrians’ awareness of specific traffic hazards. But, at the same time, road familiarity can lead to overconfident behavior and to an illusionary feeling of control. Hamed (2001) observed pedestrians who live in the vicinity of a particular intersection (and hence are more familiar with it). He found that people in a familiar setting were more reluctant to adhere to strict rules. Consistent with this finding, Rosenbloom et al. (2007) showed that in familiar locations, road users performed more traffic violations and exhibited more dangerous behavior than those in non-familiar areas. 1.5. Research rationale Building on the factors discussed thus far, the present study sought to examine pedestrians’ behavior – specifically, crossing on a red light – in their natural environment (secular pedestrians in a secular city and Ultra-Orthodox pedestrians in an Ultra-Orthodox city) and in a foreign environment (secular pedestrians in an UltraOrthodox city and Ultra-Orthodox pedestrians in a secular city). Based on previous findings (Rosenbloom et al., 2004) we predicted that Ultra-Orthodox pedestrians (described above) would cross the street on red lights more often than secular pedestrians would, and that pedestrians in the Ultra-Orthodox location would cross on red lights more often than pedestrians in the secular area would. We also expected that the dominant behavioral pattern in each location would affect the road behavior of non-local pedestrians. Additionally, based on the fact that higher average traffic volumes at intersections are associated with more pedestrian crashes
(Lee and Abdel-Aty, 2005) and that both vehicle and pedestrian volumes are positively associated with pedestrians’ tendency to cross on red lights (Rosenbloom, under review), it was expected that these parameters would affect pedestrians’ road behavior as well. 2. Method 2.1. Participants In total, 995 pedestrians were observed, of whom 515 were females (51.8%) and 480 were males (48.2%). Of the participants, about 8% (85) were children, 9% (90) were teenagers, 40% (420) were within the age group of 20–60 and the rest – about 43% (400) – were above the age of 60. In the Ultra-Orthodox city, 461 pedestrian were observed, of whom 384 were Ultra-Orthodox and 77 were secular. In the secular city, 534 pedestrian were observed, of whom 433 were secular and 101 were Ultra-Orthodox. Ultra-Orthodox people are wearing very typical dressing in near to 100% of the cases: Men are dressed with white shirts, black suits even in the hottest days of the Israeli summer and of course with one of some kind of hat on their head. Mostly, Ultra-Orthodox males have beard. Women wear long sleeve shirts, long skirts, socks and a hat or a wig on their head (Ribner, 2003). In an inter-observer validation procedure we trained the observers to define the UltraOrthodox pedestrians. 2.2. Instruments—the observation grid An observation grid, designed specially for this study (founded on the grid described in Rosenbloom et al., 2004), was planned to register the behavioral parameters of the pedestrians participating in the study. The data included variables such as estimated age, gender, religiosity, location (religious/secular), the duration of the red light, the number of vehicles crossing and the number of pedestrians waiting at the curb. Two dependent variables were registered for each participant: her decision whether or not to cross on a red light and the duration of her wait at the curb before crossing. 2.3. Location The observations were conducted in two cities, similar in population size, in the center of Israel (Bnei Brak and Petach Tikva). The crosswalks chosen for observation were both in urban settings; both were lighted pedestrian crossings on undivided streets. One crosswalk (in the Ultra-Orthodox city) was eight meters wide, the other (in the secular city) nine meters wide. Both were on twolane one-way streets. In both locations the duration of red lights was 52–53 s on average. The vehicle volume was 456 vehicles per hour and the pedestrian volume was 166 pedestrians per hour. The average number of vehicles crossing the intersections while the pedestrian light was red was 11.4 (S.D. = 4.06, min = 1, max = 22). These statistics were similar in both locations. The locations, the times of day suitable for conducting the study and the observation grid were tested in a pilot study. The two locations were chosen after many trials aimed at finding suitable crosswalks with optimal volumes of vehicles and pedestrians which was within the limits of an accurately and reliably observed. Data provided by the Police Traffic Department indicated that both locations had similar traffic volumes. This related to the same period of the day, time of year, weather conditions as that of the data collection, at either or both locations. None of these occasions of observations was related to special events. In both cities the crosswalks chosen were centrally located on routes that serve shopping venues, medical services, schools, etc.
T. Rosenbloom et al. / Accident Analysis and Prevention 40 (2008) 1919–1924 Table 1 A summary of the prediction results
Actual waited Actual crossed Overall percentage
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groups of 8, 72 in groups of 9, 50 in groups of 10, 33 in groups of 11 and 24 in groups of 12.
Predicted waited
Predicted crossed
Percentage correct
778 181
19 17
97.6 8.6 79.8
3. Results
No exceptional demographic features such as age, occupation or socio-economic status had any dominance at these locations. (This is of course important for our confidence level in the generalization power of the results.) 2.4. Procedure The study was carried out in eight sessions of one hour each, from 12:00 to 13:00 P.M. on the same days of the week. The weather was warm and pleasant during all sessions. Five trained observers stood by the side of the road and unobtrusively collected data about the pedestrians’ crossing behavior on red lights. These observers employed the following arrangement: one was responsible for observing children and young pedestrians, the second for observing adult pedestrians, the third for observing elderly pedestrians; the forth and the fifth observers were responsible for tracking the total number of pedestrians crossing the road and the total number of vehicles passing by, respectively. At the end of each session, the total numbers of the pedestrians recorded by first, second and third observers, was compared to the total number of pedestrians recorded by the forth observers. All in all, these comparisons were close to perfect. This procedure has been conducted in order to minimize the possibility that on of the pedestrians would be recorded twice by two different age-group-recording observers or omitted altogether. The observers were carefully trained to carry out the study properly: they were instructed on standardizing their criteria for classifying participants as “red light crossers” or “green light crossers” (red light crossers were those who started to cross when the light was already red) and for measuring the length of pedestrians’ waits before crossing. In an inter-observer process they were trained to record the pedestrians by the definition of “group” as people who are waiting to cross at the same time since the light has been changed to red. They were also trained to estimate the age group of the participants and to classify them as belonging to one of the four groups used: under 20 (children and teenagers), 20–60 and over 60. The training included 10 trials during which the observers estimated the ages of people from each age category and later compared their estimations with the subjects’ real ages. The average pedestrian group size was 5.84 (S.D. = 2.59). Eighteen pedestrians waited alone, 69 in pairs, 114 in trios, 132 in groups of 4, 145 in groups of 5, 144 in groups of 6, 146 in groups of 7, 48 in
Of the 995 pedestrians observed in this study (overall, in both sites), 198 (19.9%) crossed on red lights. Of these 198, 91 (45.9%) were secular and 107 (54.1%) were Ultra-Orthodox (chisquare = 2.77, d.f. = 1, p > 0.1), 81 (40.9%) were observed in the secular city and 117 (59.1%) in the Ultra-Orthodox city (chisquare = 16.18, d.f. = 1, p < 0.001). The main interest of this study, in line with previews research, is the influence of age, gender, religiosity, location and number of pedestrians waiting to cross on tendency to cross on a red light. Number of vehicles at the intersection and duration of the red light was also introduced as control but as we are also interested in these variables, as they have implications for decision making processes. And finely, we introduced in to the analyses the interaction of religiosity and location in line with the introduction. A binary logistic regression analysis (using SPSS) was performed with Tendency to cross on a red light as the dependent variable and Age (children and teenagers vs. adults and elderly), Gender, Religiosity, Location, Number of pedestrians waiting to cross, Number of vehicles at the intersection, Duration of the red light (24–64 min vs. 70 min) and the interaction between Religiosity and Location as predictor variables. A total of 995 cases were analyzed and the full model significantly predicted the tendency to cross on a red light (omnibus chi-square = 108.65, d.f. = 8, p < 0.001). The model accounted for between 10.4 (Cox & Snell R Square) and 16.4 (Nagelkerke R Square) of the variance in tendency to cross on a red light, with 97.6% of the pedestrians who waited for a green light successfully predicted; however, only 8.6% of the predictions for the pedestrians who did not wait were accurate (see Table 1). Overall 79.9% of the predictions were accurate. Table 2 presents the coefficients, the Wald statistic and the associated degrees of freedom and probability values for each of the predictor variables. It shows that Gender, Number of pedestrians waiting to cross, Number of vehicles at the intersection and the interaction of Religiosity and Location reliably predicted tendency to cross on a red light. The values of the coefficients reveal that an increase of one pedestrian in the waiting group is associated with a decrease in the odds of crossing on a red light by a factor of 0.73 (as noted in Section 4), and that an increase of one vehicle is associated with a decrease in the odds of crossing on a red light by a factor of 0.95. In addition, males were more likely to cross on red lights than females. As can be seen in Table 3 we did not find statistically significant evidence that Ultra-Orthodox pedestrians tend to cross the street on red lights more often than secular pedestrians do, or vice versa (the results were 22% Ultra-Orthodox vs. 17% secular pedestrians who crossed on red). We did find, however, an
Table 2 The coefficients for each predictor variable, the Wald statistic and the associated significant values
Age Gender Religiosity Location Number of pedestrians waiting to cross Number of vehicles at the intersection Duration of the red light Religiosity by Location Constant
B
S.E.
Wald
d.f.
Sig.
Exp(B)
−0.297 0.437 0.384 0.376 −0.305 −0.045 0.345 −1.046 0.410
0.236 0.172 0.289 0.323 0.047 0.022 0.189 0.403 0.414
1.585 6.483 1.758 1.357 43.134 4.229 3.328 6.734 0.979
1 1 1 1 1 1 1 1 1
0.208 0.011 0.185 0.244 0.000 0.040 0.068 0.009 0.322
0.743 1.548 1.468 1.456 0.737 0.956 1.411 0.352 1.506
The relative effects of these factors may be summarized by the logistic regression equation: Log odds = 0.410 − 0.297 Age + 0.437 Gender + 0.384 Religiosity + 0.376 Location − 0.305 Number of pedestrians waiting to cross − 0.045 Number of vehicles at the intersection + 0.345 Duration of the red light + 1.046 Religiosity by Location.
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Table 3 Absolute numbers of crossing and not crossing (cross/not cross ratios), for UltraOrthodox city and Secular city, and for the Ultra-Orthodox and Secular Levels of variables
Count cross/not cross
Ultra-Orthodox Secular Ultra-Orthodox city Secular city
107/378 91/419 117/344 81/453
Ultra-Orthodox city Ultra-Orthodox Secular
83/301 34/43
Secular city Ultra-Orthodox Secular
24/77 57/376
Ultra-Orthodox Ultra-Orthodox city Secular city
83/301 24/77
Secular Ultra-Orthodox city Secular city
34/43 57/376
and strong gender roles. Their socio-economic status is below the Israeli average due to low income (most men engage only in daily prayer and the study of religious texts) and large families (Ribner, 2003). It appears that to the Ultra-Orthodox Jewish population, state rules (like traffic rules) are perceived as inferior to the Jewish Halacha rules (Rosenbloom et al., 2004). 4.1. The religiosity–location interaction
interaction between Religiosity and Location. Specifically, in the Ultra-Orthodox city, 44% of the secular pedestrians, but only 21% of the Ultra-Orthodox pedestrians, crossed on a red light (chisquare = 17.20, d.f. = 1, p < 0.001). This pattern was reversed in the secular city, where 23% of the Ultra-Orthodox pedestrians, but only 13% of the secular pedestrians, crossed on red (chi-square = 7.14, d.f. = 1, p < 0.05). We also discovered that males tend to cross on red more often than females do (24% males vs. 15% females). In addition, increases in the number of pedestrians waiting to cross and increases in the number of vehicles at the intersection are both associated with a decrease in the odds of crossing on a red light. 4. Discussion This study aimed to investigate the comparative abidance of Ultra-Orthodox and secular pedestrians with traffic rules. In his Theory of Moral Sentiments, Smith (1976) analyzed religiosity from a rational point of view and noted that religiosity acts as a kind of internal moral enforcement mechanism. Mears et al. (2006) assert that religiosity may affect criminogenic factors, such as drug use. Changes in these factors may ultimately improve recidivism and behavioral outcomes among participants. Smith (2003) identified three dimensions in religiosity that may affect delinquent behavior, each of which includes three factors: (1) moral order (moral directives, spiritual experiences and role models); (2) learned competencies (community and leadership skills, coping skills and cultural capital); and (3) social and organizational ties (social capital, network closure and extra-community skills). In each case, Smith’s proposed logic is that religion reduces delinquency. The Ultra-Orthodox community observed in this research is typified by the traits described by Smith (2003), as it is an extremely religious group that endorses patterns of voluntary segregation. This Jewish community is governed by scrupulous observance of Jewish law, aimed at moving closer to God. Any deviation from divinely ordained biblical requirements is unacceptable; the community emphasizes stricter rather than more lenient legal interpretations, and these results in higher levels of spirituality. This ideology is reflected in the manner of the community members: Ultra-Orthodox people typically dress modestly and rather uniformly (particularly males). They espouse values of marriage and large families (five to ten children per family is quite common) as fundamental and preserve gender-segregated education
Our principle research question was whether the road-crossing behavior of Ultra-Orthodox pedestrians is different from that of secular pedestrians and whether such behavior depends on the environment in which it occurs. All in all, there is some evidence, though no significant evidence for it that Ultra-Orthodox pedestrians tend to commit more road violations than secular pedestrians do; at the same time, more road violations were registered in the Ultra-Orthodox location than were registered in the secular location. The most interesting finding of this research, however, is the significant interaction between Religiosity and Location. The tendency to cross on a red light was dependent on the environment. In regard to pedestrians’ traffic violations, this means that in the Ultra-Orthodox city as well in the secular city, pedestrians in an environment markedly different from their own committed approximately twice as many traffic violations as locals did. People – Ultra-Orthodox as well as secular – may feel discomfort about breaking social norms perceived as such in certain environments. Grasmick et al. (1991) argue that there are agents other than the state that can threaten violators. They argue that agents in one’s near surroundings reduce the expected utility of crime through informal and “interpersonal sanctions” (e.g., diminished respect). They state: “While embarrassment’s most immediate consequence probably is physiological discomfort, more long-term consequences include loss of valued relationships, and perhaps restricted opportunities to achieve other valued goals (p. 253).” Grasmick et al. mention feelings of shame or guilt as another factor that can reduce the violation of social norms. These sentiments may influence behavior, reducing the perceived benefits of rule violation. According to Lewis (1971), guilt arises when individuals realize that they have acted irresponsibly or in violation of a rule or social norm that they have internalized. To sum this point up, it might be that both secular and Ultra-Orthodox pedestrians feel much more comfortable about breaking traffic rules when they are not in their own neighborhoods. However, based on Rosenbloom et al. (2004) we assume that the negative safety climate in Ultra-Orthodox environment (caused apparently by the tendency of Ultra-Orthodox residents to break the traffic laws) might be adopted by bypassing strangers. 4.2. Gender A higher rate of males than females crossed the street on a red light. This trend was not influenced by the religiosity of the pedestrians. The over-representation of males vs. females in risky behavior and law-breaking has been well-documented in previous works: men report crossing on a “don’t walk” sign more frequently, and express weaker ‘instrumental’ and ‘normative’ motives for safe crossing (Yagil, 2000). Additionally, males are more risky than females both as drivers and as pedestrians and are involved in more fatal accidents (Harre et al., 1996). This finding is stable in all age groups: more boys than girls are injured on the roads, and this trend remain stable through old age (Connelly et al., 1998).
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4.3. Vehicle volume Lee and Abdel-Aty (2005) indicated that car crashes involving pedestrians are more likely to occur at intersections with higher traffic volume, which increases the potential conflicts between pedestrians and vehicles. However, it appears that the rate of increase in accidents gradually diminishes as average annual daily traffic increases. This trend is consistent with prior European models, which showed that the number of crashes involving pedestrians is approximately proportional to the square root of vehicle volume. However, the rate of increase is steeper at lower average traffic values. In the present study, an increase in the number of vehicles was found to be associated with a decrease in the odds of crossing on a red light. Although pedestrians are supposed to rely solely on traffic lights to determine whether or not to cross a lighted intersection, a judgment of how dangerous it might be to cross on red is clearly involved, though not necessarily consciously. Normally, people are more inclined to cross on a red light when they see the situation as less dangerous. Yagil (2000) found gender differences with regard to the perception of situational factors as dangerous: whereas among women, safe road crossing is perceived as predicted by the presence and behavior of other pedestrians, among men it is perceived as influenced by the traffic volume and other conditions. In other words, women are more influenced by their social environment, whereas men seem to be more concerned with the physical aspects of the setting. The current study, however, did not find any gender differences with regard to the relationship between traffic light abidance and the volume of pedestrians or traffic.
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Miller and Byrnes, 1997) who emphasize adolescents’ tendency to take more risks in the presence of peer groups. The pragmatic explanation for the higher rate of people to cross on red when waiting at the curb alone is that people are aware, from past experience, that the larger the group waiting at the curbside, the shorter the amount of time they can expect to wait until the light turns green. A quick cost-benefit calculation suggests that they invest a few more seconds in waiting so as to be on the safe side. This would suggest that it might be beneficial for traffic lights to display the amount of time that remains until the light is to turn green. From another pragmatic point of view, large groups of pedestrians crossing together on red may feel safer than individuals do because of the “safety in numbers” effect that may occur when many pedestrians cross simultaneously. Additionally, pedestrians may assume that oncoming traffic is better able to see them and more likely to come to a stop when there are many people huddled at the crosswalk, and this may encourage more crossing as well. Consequently, greater trust may be placed in drivers under these conditions, reducing the perceived need for caution by pedestrians. The most interesting finding of this research is that in both locations, “foreigners” committed more traffic violations than “natives” did. Additional findings were that the larger the group of the people waiting on the curbside, the lower the rate of people crossing on a red light; and that an increase in vehicle volume was associated with a decrease in the odds of crossing on a red light. Consistently with previous research, males crossed on red much more often than females did, regardless of religiosity and location. 4.5. Methodological remarks
4.4. Pedestrian volume The current study found that the larger the group of people waiting at the curb, the lower the rate of people to cross on a red light. A few reasonable explanations elucidate this pattern; one is theoretical, the others pragmatic. Hirschi’s Social Control Theory (Hirschi, 1969) suggests that the mechanism behind obedient behavior is people’s motivation to be rewarded simply for conformism. Normal individuals have buffers that prevent them from breaking the law and therefore encourage them to behave in a normative way. The sanctions administered by society are much more of a deterrent for normative people than formal sanctions are (Hirschi and Gottfredson, 1994). Thus, people who arrive at a crosswalk alone on a red light are not concerned about social criticism and are therefore more likely to break the law; while those surrounded by other pedestrians feel much more committed to the social order and to social norms. If this is true, this tendency might have potential beneficial implications. Hirschi (2004) assumes that the strengthening of individuals’ bonds to conventional institutions of society might increase their commitment to normative behavior. Authorities should therefore employ this principle in order to increase self-control and with it normative, safe behavior. This pattern has exceptions. A comprehensive project (BenMoshe, unpublished thesis work) that examined the road-crossing decisions of young children and adolescents (6-, 9- and 13-year-old boys and girls) revealed a converse trend: each participant standing at a crosswalk with his or her peer group was much more willing to take risks while crossing than the same participant was while crossing alone. Thus, the mechanism of social facilitation (Corston and Colman, 1996; Sanna and Shotland, 1990) works differently when children (pre-adolescents) are involved. Support for this notion is supplied by researchers (Christenson and Morrongiello, 1997;
Field settings, such as that used in the present study, have obvious advantages, but certain limitations as well. The conditions in a natural setting constrain the ability of the observers to measure some relevant behavioral parameters, such as the exact waiting time at the curb, problematic operational definitions, pertinence to age and culture groups’ estimations, and uncertainty of the control for traffic volume. Another interesting piece of information lost in the present study is the probable interaction between foreign and local citizens waiting for the light to change: Who is the first to cross the street on red and what is the reaction of the others? Special equipment could solve such problems in further research. Beyond such technical problems, one must take into consideration that the theoretical explanations offered to the Ultra-Orthodox pedestrians’ relatively unsafe road behavior can stem from their cultural conventions rather than from their religiosity; though the two are hard to differentiate. Larger families living in worse financial conditions may pay less attention to rules (Park, 2007), including traffic rules. 4.6. Practical implications The unique dynamics of the mixed group on the curb (UltraOrthodox and secular pedestrians) may reflect the tendency of people to absorb the cultural (safety) climate of their environment (Guldenmund, 2000). As mentioned above, religious laws are perceived by religious people as more compelling than state laws (Yagil and Ratner, 2002), and this may be why Ultra-Orthodox pedestrians flout traffic rules more often than secular people do; yet strangers who happen to arrive in an Ultra-Orthodox neighborhood may modify their behavior so as to “fit in” with the locals. This trend must be taken into consideration in the planning of educational campaigns aimed at changing road behavior.
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