Shane Brady
email: shane.brady.1@ucdconnect.ie

Adriana Hava

Philip Perry

John Murphy

Damien Magoni
email: damien.magoni@u-bordeaux.fr

A Omar Portillo-Dominguez
email: andres.portillodominguez@ucd.ie

Towards an Emulated IoT Test Environment for Anomaly Detection using NEMU

Keywords: Internet of Things, Emulation, Testing, NEMU

The advent of the Internet of Things (IoT) has led to a major change in the way we interact with increasingly ubiquitous connected devices such as smart objects and cyberphysical systems. It has also led to an exponential increase in the number of such Internet-connected devices over the last few years. Conducting extensive functional and performance testing is critical to assess the robustness and efficiency of IoT systems in order to validate them before their deployment in real life. However, creating an IoT test environment is a difficult and expensive task, usually requiring a significant amount of physical hardware and human effort to build it. This paper proposes a method to emulate an IoT environment using the Network Emulator for Mobile Universes (NEMU), itself built on the popular QEMU system emulator, in order to construct a testbed of inter-connected, emulated Raspberry Pi devices. Additionally, we experimentally demonstrate how our method can be successfully applied to IoT by showing how such an emulated environment can be used to detect anomalies in an IoT system.

I. INTRODUCTION

Internet of Things (IoT) has become a major technological revolution which is leading to an explosive growth in the number of internet-connected devices globally. Experts estimate that IoT will consist of approximately 50 billion devices by 2020 [START_REF] Evans | The internet of things: How the next evolution of the internet is changing everything[END_REF]. Consequently, IoT is gradually impacting every business area and industry field. Moreover, how effectively these devices are able to communicate (particularly over potentially heavily congested networks) can have a major impact on the quality of the services provided, as well as in their degree of success (or failure). Therefore, properly testing such IoT services is essential [START_REF] Weber | Internet of things new security and privacy challenges[END_REF]. However, testing in IoT is a very challenging task. This is because the intrinsic characteristics of IoT (e.g., the normally vast number of devices and the complex nature of the inter-connectivity among the devices) make the creation of an appropriate test environment of real devices particularly effort-intensive and costly. Likewise, monitoring the health and performance of an IoT system presents similar challenges. This is the result of producing and transmitting huge amounts of data, which makes considerably more complex the detection of anomalous behaviours within the system.

To address these challenges, our research work has focused on developing techniques to improve the processes involved in testing IoT solutions, with a special interest on anomaly detection. In particular, this work presents a novel method to create an emulated IoT environment based on the Network Emulator for Mobile Universes (NEMU), which is a powerful state-of-the-art tool used to create highly customisable virtual networks of virtual machines [START_REF] Autefage | Nemu: A distributed testbed for the virtualization of dynamic, fixed and mobile networks[END_REF]. This work also shows, through experimental evaluation, how the emulated environment can produce similar results when used at specific settings (compared to a real one), while also significantly simplifying the effort required to build a test environment. This was assessed within an anomaly detection scenario, in which the health of the IoT systems was monitored with log analytic techniques.

II. RELATED WORK

Several research works have focused on developing techniques to simulate IoT environments. For example, the authors of [START_REF] Silva | Cidrarchy: Cidr-based ns-3 routing protocol for large scale network simulation[END_REF] presented an approach to improve the scaling capabilities of the NS3 simulator, so that it is usable for large problem sizes (such as IoT). Despite the fact that simulations are useful to test IoT advancements to a certain degree, they are not suitable for all scenarios. For instance, when the IoT services need to be tested in real-time to assess if they can fulfill their expected Service Level Agreements. Consequently, other works have focused on emulating IoT environments where applications can be deployed and executed exactly as they would in real life. Despite the progress in this area, there is still a need for approaches that allow to create more easily, and with less effort, emulated IoT systems [START_REF] Vilen Looga | Mammoth: A massive-scale emulation platform for internet of things[END_REF]. This is because most of the current alternatives are typically hard to use, and difficult (or impossible) to configure at run-time. In 2015, Bagula and Erasmus have proposed an IoT emulation environment with COOJA [START_REF] Bagula | Iot emulation with cooja[END_REF]. However, this environment is targeted only at Contiki systems and emulate motes such as Tmote Sky, Z1 mote, MicaZ mote, etc. It can not be used for Raspberry Pi emulation. More recently, Le-Trung has proposed an IoT testbed emulated over an OpenStack Cloud infrastructure [START_REF] Le-Trung | Towards an iot network testbed emulated over openstack cloud infrastructure[END_REF]. However, his testbed is based on the QOMET emulator which uses wireconf, a software only available on RHEL6 systems.

For these reasons, this paper presents a method that leverages on NEMU to improve that process. NEMU is a tool to create (and manage) realistic virtual dynamic networks, allowing practitioners to test and evaluate prototypes of complex applications (such as IoT services) with a complete control over the characteristics of the emulated environment (e.g., network topology and link parameters). Also, NEMU can create such environments with relatively limited hardware resources, without any administrative rights, and/or distributed over several physical machines [START_REF] Autefage | Nemu: A distributed testbed for the virtualization of dynamic, fixed and mobile networks[END_REF]. As NEMU uses QEMU for system emulation, it can run a large variety of hardware including Raspberry Pis. For these reasons, NEMU is an attractive candidate to be used in the IoT domain. Finally, anomaly detection is a relevant scenario in IoT, where sensor data and sensor faults are continuously monitored. For instance, the authors of [START_REF] Jayavardhana Gubbi | Internet of things (iot): A vision, architectural elements, and future directions[END_REF] presents a comprehensive list of potential solutions to discover anomalies (e.g., using supervised and unsupervised machine learning techniques). In contrast to other works in the area, this work proposes the usage of log analytic techniques to detect such anomalies.

III. PROPOSED METHOD

A. Testbed Architecture

The architecture of the IoT testbed (i.e., the emulated IoT environment) contains multiple components:

1) NEMU is used for the creation and management of a network of virtual machines (VM). An important characteristic of NEMU is that it allows to modify the system at run-time. For instance, by allowing to add (or remove) devices to the network, as well as network links between the devices. This capability allows the introduction of anomalies into the IoT system. 2) QEMU is used to emulate the IoT devices (e.g., Raspberry Pis in our case). QEMU was chosen because it is an open source machine emulator that allows to accurately emulate an IoT device (especially the processor, such as the ARM family of low power processors typically used in SoC-based boards). Alternatively, the practitioner can also use real IoT devices and hook them to the virtual network. This is useful if some specific hardware can not be emulated, such as specific shields. These components are shown in Fig. 1, which depicts the high-level architecture of the testbed.

B. Testbed Generation

The following steps are required to create a working emulated IoT environment:

1) Define the network topology. For this work, we focused on the widely-used tree topology [START_REF] Bishnu Kumar Maharjan | Tree network based on bluetooth 4.0 for wireless sensor network applications[END_REF], [START_REF] Kim | Bluetooth-based tree topology network for wireless industrial applications[END_REF] typically used to manage large scale networks. However, any topology can be built with NEMU. At the bottom of the tree structure, there are sensors constantly monitoring and reporting their measured values. On the next layer up there are a series of Raspberry Pis, each responsible for a cluster of sensors. Raspberry Pis are used as they are small, affordable computers, widely deployed in IoT environments. As we proceed up the tree, each higher level Raspberry Pi is responsible for a number of Raspberry Pis below it in the tree. Each Raspberry Pi will report both the sensor data it receives, as well as metrics about the performance of the device itself up the tree. These metrics, including the CPU and memory usage of the device as well as network statistics (such as throughput, packet loss and latency) provide insight into the health of the system as a whole, enabling the detection of anomalies in the network. 2) Create Virtual Host Configurations (VHostConf object in NEMU). Each VHostConf acts as a template For Virtual Hosts (VHost object in NEMU) to expedite the generation of VMs (based on the templates). 3) Specify the architecture (e.g., ARM), the processor (e.g., arm1176) and to provide the kernel for the chosen operating system. 4) Create VHosts that represent the devices (i.e., Raspberry Pis). For each VHost, the experimenter can modify the configuration parameters defined on the VHostConf. A virtual drive image must be provided for the host (i.e., Raspbian Wheezy). 5) Specify the parameters for the virtual Network Interface Cards (VNics). (VRouters) to simplify the management of the network. A VRouter provides services such as DHCP and IP forwarding. A VRouter can also be linked to a VSlirp. A Slirp is a particular virtual point-to-point link which enables a VHost to communicate with the Internet through NAT emulation inside QEMU. Slirp links also contain internal DHCP and DNS servers. This capability is needed to send information from the emulated IoT system to a machine outside of the virtual network (e.g., on the Internet). 8) An optional step is to connect real hardware devices to the emulated network (as shown in Fig. 1). This is done by creating a Linux bridge and a TAP interface on the machine hosting the testbed (i.e., where the QEMU devices are being created). The TAP interface allows software in the Linux user space to be able to use a virtual Ethernet interface on the host machine. A real device can be connected to the host either straight into the host physical NIC or through a physical switch as shown on the figure. Both the host's NIC and the TAP are then connected to the Linux virtual bridge thus creating an hybrid virtual/real network. Finally, to complement the previous discussion, Fig. 2 presents an exemplary tree topology created using the above discussed method.

C. Anomaly Detection Use Case

Among the range of available use cases, our work has initially focused on anomaly detection due to its relevance to IoT. In this scenario, an IoT system, composed of multiple devices interconnected through a network topology, periodically transmits their data to a consumer layer such as a NodeRED application. This layer is then responsible for consolidating the received data (potentially from several IoT systems) before sharing it to an analytics service, such as Logentries's log analytics platform, with the aim of identifying abnormal behaviours that might occur in the system.

D. Log Analytics Platform

To interface with the anomaly detection logic, the device at the top of the topology (i.e., the root of the tree) is set responsible for forwarding the sensor data and usage metrics of all devices in the topology from the IoT system to a NodeRED application. It runs independently on its own machine and is used to share the data to a real-time log analytics platform (e.g., Logentries), where the data is analysed to detect anomalies in the IoT system. The NodeRED application can also generate logs (i.e., reflecting its own performance), information which can be correlated with the other logs to deepen the detection of anomalies. Fig. 3 shows the temperature values and anomalies reported in the log analytics system (i.e., Logentries). Temperatures below 19.6C and above 20.4C are flagged as warnings (see section IV).

IV. EXPERIMENTAL EVALUATION

The performed experiments aimed to assess how well an emulated IoT system created with our proposed method and software was able to act as a real one. For this purpose, experiments addressed three scenarios:

1) Measurements of an IoT application using the MQTT protocol. 2) Processor and memory usage of a benchmark application. 3) Network throughput of iperf and FTP applications.

A. Setup

Three types of experiments were done: 1) The first type used a real IoT system built with Raspberry Pi hardware. This real environment was composed of Raspberry Pi 3, model B, and connected by a 100 Mbps Ethernet switch.

2) The second type used an emulated IoT system built with ARM emulation software performed by the QEMU system emulator. The emulated environment was composed of the same number of equivalent emulated Raspberry Pis, using a QEMU specific kernel 1 and Raspbian Wheezy as the Operating System (OS).

3) The third one used a virtualized IoT system built with x86-64 virtualization performed by the QEMU-KVM virtualization software.The virtualized environment was composed of x86-64 virtual machines leveraging VTx hardware acceleration through the KVM module and running Debian Wheezy as OS. As the Raspbian distribution used on Raspberry Pis is based on the Debian distribution, these VMs may run code compiled for the same major release without problems. Both emulated and virtualized environments were running on a Dell Precision T5500 workstation equipped with an Intel Xeon at 2.40Ghz (4 cores/8 threads), 24 GB of RAM, under Linux Ubuntu 15.10 64-bit. All experiments were done in isolation, so that all load was controlled. Also, we used LogEntries as real-time log analytics platform due to its strong analytic capabilities [START_REF] Siniarski | Realtime monitoring of sdn networks using non-invasive cloud-based logging platforms[END_REF].

Two representative anomaly detection scenarios were evaluated: sensor temperature warnings and processor and memory load warnings as already discussed in section III-C. The sensor temperature data was simulated by using a script which randomly generated temperature values by following a normal distribution centered at 20 C and a 2σ of 0.2 C. It ran on the devices found on the leaf nodes of the network, transmitting this information along with the other metrics. To generate processor and memory loads, we introduced some controlled noise to the system by running on the devices a subset of the widely-used Java Dacapo benchmarks [START_REF] Portillo-Dominguez | Trini: an adaptive load balancing strategy based on garbage collection for clustered java systems[END_REF].

As evaluation criteria, the main metrics were temperature measurements and anomaly detection, processor and memory usage (in %), and network throughput (in Mbps). These metrics were collected with the following tools: wireshark (for MQTT packets) and Logentries (for anomalies), htop and psutils (for processor and memory usage), iperf and the GNU/Linux ftp client (for network throughput). Monitored events (i.e., detected anomalies) were retrieved from LogEntries' reports, which was fed by the NodeRED node. Temperature readings below or above 2σ of the mean were considered as anomalies and flagged as warnings.

B. Results

1) Experiment 1 -MQTT-based IoT application:

The MQTT protocol was used to send messages from fake temperature sensors running on the Raspberry Pis to an MQTT broker (server). MQTT runs on the TCP protocol thus it is reliable at the transport layer. We have used the QoS setting of 0 for MQTT which means that messages are send in best effort mode at the application layer. Fig. 4 shows the temperature measured and sent in the real IoT system over time. Fig. 5 shows the temperature measured and sent in the emulated IoT system. For this experiment, each run fired 1800 messages (lasting around 30 mn when firing 1 message per second), and 10 runs were performed per testbed type. Min, max and average values are shown on the figures. We can observe that the received values are similar and not affected by the type of testbed used. We have observed that for each type no messages were lost and no messages were delivered out of order. This means that the server has not lost any received message. Only the fact that random values produced by a normal distribution were used as inputs (temperature values) explains the variations on the figures. We haven't shown the results produced by the virtualized testbed as they are similar to both figures already shown. We have also observed the total duration for firing the 1800 messages. We have tested with various message rates from 0.1 to 100 per second. We have collected those values in Table I. We notice that the total time for sending those messages are matching the frequency parameter for the real and virtualized testbeds. The virtualized testbed is a bit faster because hardware accelerated x86 virtual machines are faster than real RPis. The emulated testbed performs similarly at low message frequencies but shows an increased lag when the frequency increases. At 100 messages per second, the emulated testbed is 86% slower than the real one. This issue must be taken into account when using the emulated testbed and depends on the IoT application used. In most cases, 1 message per second would be considered high, but in some cases, monitoring may require up to 100 messages per second, maybe more.

To understand the behaviour of the systems across the evaluated experimental configurations, our analysis focused on comparing the number of anomalies detected per environment as shown in Table II. It can be noticed how the number of detected anomalies over half-an-hour (at 1 message/s) exhibited a comparable behaviour regardless of the type of

Fig. 1 .

 1 Fig. 1. High-Level Architecture

Fig. 2 .

 2 Fig. 2. NEMU Scripting Components

Fig. 3 .

 3 Fig. 3. Temperature data reported at the log analytics platform

Fig. 4 .Fig. 5 .

 45 Fig. 4. Temperatures reported by the Physical Raspberry Pi Network

https://github.com/dhruvvyas90/qemu-rpi-kernel

ACKNOWLEDGMENT Supported, in part, by Science Foundation Ireland grant 13/RC/2094. Supported, in part, by Agence Nationale de la Recherche grant ANR-10-IDEX-03-02.

test environment. Results for the real network are more spread out as shown by the higher standard deviation values, due to the use of real network hardware. An example of the observed anomalies (i.e., temperature thresholds) at Logentries is depicted in Fig. 3. 2) Experiment 2 -processor and memory intensive application: A second set of experiments was performed to assess the behaviour of our solution in more resource-intensive scenarios, where one or more resources, such as CPU or memory, would frequently reach 100% usage. Even though such scenarios might not be the most commonly found in IoT (as the data gathering and processing usually tend to be light-weight in terms of CPU and memory), the aim was to strengthen the validation of our solution by identifying either other potentially applicable usage scenarios or limitations on its usage. The experimental set-up was similar to that used in the previous experiment, with the following difference: instead of using MQTT, the tested devices ran a subset of the widely-used Java Dacapo Benchmarks [START_REF] Portillo-Dominguez | Trini: an adaptive load balancing strategy based on garbage collection for clustered java systems[END_REF]. This strategy allowed us to diversify the assessed behaviours (i.e., CPU and memory usage) by introducing some variability on the workloads processed by the system. The chosen benchmark programs were luindex, sunflow and eclipse, which used three considerably different levels of resource utilization. Each test run lasted 10 minutes and was repeated 10 times. All the plots show for each timed data point (one per second), its average, min and max values over the 10 runs.

Obtained results are illustrated in Figures 6,7, and 8. They show how an experimental configuration behaved on each of the three tested types of environments. Intuitively, if the figures depicted similar shapes among them (like in the previous experiment), the environments would exhibit a comparable behaviour. However, it can be easily seen, by visually inspecting the figures, that it is not the case. Figure 6 depicts the real Raspberry Pi, hence, this exemplifies a baseline behaviour. Meanwhile, Figure 7 and 8 depict the emulated and virtualized Raspberry Pi networks, respectively. It can be noticed how the trends in Figure 8 (i.e. the three peaks caused by the execution of the chosen benchmarks) resemble the ones of the real Raspberry Pi, although they are less sharp.

Furthermore, it can be noticed how the trends depicted on 7 considerably differentiate against the other two figures. In the case of the CPU, its usage practically reaches 100% during the three peaks, situation which indirectly influenced the memory usage (which showed a relatively flat behaviour). This is due to the software-only emulation of the ARM processor which is very demanding for the host environment.

3) Experiment 3 -network intensive application: The last experiment focused on measuring network throughput between the devices in each testbed type and also between different types (e.g., between a physical Raspberry Pi (RPi) and an emulated RPi). These results are summarized in Table III, depicting the throughput obtained for each combination of the three tested environment types. Considering that the first line in the table (i.e., RPi → RPi) is the performance baseline, it can be noticed how, whenever an emulated RPi is involved, there is a drastic reduction in throughput (e.g., of approximately 75% in the case of the FTP traffic). This is because in these scenarios, the relatively slowness of the emulated RPi makes it to become a bottleneck in the system (hence provoking the observed impact on throughput). In contrast, it is worth noticing that, even in such saturated scenario, a virtualized x86-64 works fine as a replacement of a real Raspberry Pi. This is reflected in the fact that all combinations using a virtualized x86 achieved levels of throughput comparable to the corresponding baseline value. The only exception was the experimental configuration which only used virtualized environments. This was the result of using hardware acceleration and not capping the NEMU links (i.e., letting them reach maximum throughput), which made the system achieve a throughput higher than what would be actually possible with the real hardware. V. CONCLUSION Performing proper testing in IoT is very challenging. In particular, creating a real testing environment is difficult and expensive. This is because a large amount of human effort and investment in hardware are typically required to create such environments. To address this problem, this paper proposed a novel method to create a realistic emulated IoT testing environment, based on NEMU (a state-of-the-art network emulator). The aim is to increase IoT practitioners' productivity by facilitating the creation of suitable IoT testing environments in which IoT advancements can be easily tested during their research and development cycles. That is, before their level of maturity justify the costs involved on testing in a real IoT environment.

Our experimental results have shown how such emulated environment closely resembles a real IoT environment, as both types of environments produced similar results when used for IoT applications. However, results also showed that processing and memory intensive applications shall not be evaluated by emulation as the performances are still widely different from a real system. Practitioners should therefore check that the IoT application under test is not stressing the devices in terms of processing, memory or network bandwidth, otherwise results obtained on the emulated testbed will be incorrect.

These experiments were done within a log analysis context, where the aim was to monitor and detect anomalies in the IoT environments in real-time. The overall results showed that the emulated IoT system worked well, as the behaviours of the detected anomalies (across all the tested experimental configurations) were similar between the two environments, as they achieved comparable numbers of anomalies.

Future work will focus on strengthening the experimental validation of our approach. For instance, by diversifying the characteristics of the emulated environment (e.g., topologies, number of nodes, link characteristics). Additionally, we plan to investigate ways to improve the detection (and potentially the alleviation and/or elimination) of the anomalies discovered in the IoT system.


est destinée au dépôt

  Hybrid numerical method associating a conformal transformation of the complex plane with a matrix formulation for the calculation of the eigenvalues andeigenvectors in bended waveguides Lucas Garnier, C. Saavedra, Rigoberto Castro-Beltran, Giuseppe A Cirino, José Luis Lucio, Bruno Bêche To cite this version: Lucas Garnier, C. Saavedra, Rigoberto Castro-Beltran, Giuseppe A Cirino, José Luis Lucio, et al.. Hybrid numerical method associating a conformal transformation of the complex plane with a matrix formulation for the calculation of the eigenvalues andeigenvectors in bended waveguides . Progress In Electromagnetics Research Symposium -PIERS 2017, May 2017, St Petersbourg, Russia. pp.435. hal-01527937


Juergen Bracht
email: juergen.bracht@abdn.ac.uk.

Adam Zylbersztejn
email: zyl-bersztejn@gate.cnrs.fr.

Daniel Bartels

Astrid Hopfensitz

Michal Krawczyk

David Masclet

Ernesto Reuben

Moral Judgments, Gender, and Social Preferences: An Experimental Study

Keywords: Gender, moral dilemmas, moral judgments, spite, antisocial attitudes, experiment C91, D03, D63 Moral Judgments, Gender, and Social Preferences: An Experimental Study Moral Dilemma, Moral Judgments, Experiment, Gender, Anti-social Preferences, Confounding Variable, Individual Dierence. JEL Classication: C91, D03, D63

We study questionnaire responses to moral dilemmas hypothetical situations in which sacrificing one life may save many other lives. We demonstrate gender differences in moral judgments: male participants are more supportive of the sacrifice than female participants. We investigate the importance of the previously studied source of the endorsement of the sacrfice: antisocial attitudes. First, we elicit the individual proneness to spiteful behavior using an incentivized experimental game. We demonstrate that spitefulness can be sizable but it is not associated with gender. Second, we find that gender is associated with moral judgments even when we account for individual differences in antisocial attitudes. Our results suggest that the performance of many institutions (related to the distribution of wealth or punishment, for instance) may be affected by the gender of the decisionmakers.

Introduction

In our paper, we look at questionaire responses to moral dilemmas situations in which inicting harm on one person allows many others to escape suering. Many examples illustrate this kind of dilemma. During social unrest, framing an innocent person may prevent people make ethical judgments they may be informed by their instant feelings of agreement or disagreement [START_REF] Haidt | The Emotional Dog and Its Rational Tail: A Social Intuitionist Approach to Moral Judgment[END_REF], (2003)). A recent line of research on moral dilemmas investigates whether moral judgment is associated with gender, and how moral judgement is related to anti-social attitudes. A rst set of papers concludes that there are gender dierences in moral judgment; men are more prone to endorse the utilitarian solution in hypothetical moral dilemmas. The ndings are reported in Petrinovich, O'Neill and Jorgensen (1993), Zamzov and Nichols (2009), Banerjee, Huebner, and [START_REF] Banerjee | Intuitive Moral Judgments are Robust Across Demographic Variation in Gender, Education, Politics, and Religion: A Large-scale Web-based Study[END_REF] and [START_REF] Buckwalter | Gender and Philosophical Intuition[END_REF], among others. In addition, [START_REF] Hsu | The Right and The Good: Distributive Justice and Neural Encoding of Equity and Eciency[END_REF] report that men tend to favor the utilitarian solution in a real-world moral dilemma more than women: a choice of actual allocation of meals among poor African kids through a charity organization. [START_REF] Banerjee | Intuitive Moral Judgments are Robust Across Demographic Variation in Gender, Education, Politics, and Religion: A Large-scale Web-based Study[END_REF] On the other hand, a replication study by [START_REF] Seyedsayamdost | On Gender and Philosophical Intuition: Failure of Replication and Other Negative Results[END_REF], and studies of [START_REF] Gold | Cultural Dierences in Responses to Reallife and Hypothetical Trolley Problems[END_REF][START_REF] Gold | Do as I Say, Don't Do as I Do: Dierences in Moral Judgments Do not Translate Into Dierences in Decisions in Real-life Trolley Problems[END_REF] report no systematic gender dierence in moral judgements. Interestingly, a large study by [START_REF] Hauser | A Dissociation between Moral Judgments and Justications[END_REF] with over 2000 participants does nd large and signicant gender dierences for each of the moral dilemma, and reports no gender dierences only when comparing responses to paired scenarios. Another large study by [START_REF] Bourget | What Do Philosophers Believe?[END_REF] nds a number of gender dierences, including women being less likely to agree with the utilitarian solution in a moral dilemma.

5

The second set of studies points to a somewhat counterintuitive conclusion that people with anti-social attitudes are prone to make utilitarian judgments. [START_REF] Koenigs | Damage to The Prefrontal Cortex Increases Utilitarian Moral Judgments[END_REF] conducted a study of brain-damaged patients with acquired sociopathy. These kind of emotional decits are similar to those observed in psychopaths (Saver and Damassio (1991)).

These kind of patients are found to display unusually high levels of endorsement of the utilitarian solution to moral dilemmas. In the same vein, Glenn et al (2010) report that psychopathic traits measured using Levenson's Self-Report Psychopathy Scale predict a stronger endorsement of utilitarian solutions across several moral dilemmas.

Finally, [START_REF] Bartels | The Mismeasure of Morals: Antisocial Personality Traits Predict Utilitarian Responses to Moral Dilemmas[END_REF] in a study most closely related to ours report gender dierence in moral judgments as well (in a large set of moral dilemmas that we also employ herein). However, their report also highlights the importance of individual traits: there is a positive relation between endorsement of sacrice-one-live-to-save-many-lives and measures of psychopathic personality (low empathy, callous aect, and thrill-seeking), Machiavellianism (cynical, emotionally detached from others, and manipulative), and perceived life meaninglessness (melancholic existential concerns). Furthermore, they nd that men tend to score higher in all of those psychological questionnaires, and that the gender eect on moral judgments fades away when psychological traits are accounted for. Their nding, in turn, raises the question of whether the relationship between moral judgment and gender is spurious because the research failed to account for anti-social traits as a confounding factor.

In our paper, we ask a novel question, and investigate the interaction between moral judgments, gender, and other-regarding preferences in moral dilemmas. We elicit the propensity for other-damaging behavior (spitefulness) using an experimental game, and use our measure as a control when we explain gender dierence in responses to a moral-dilemma questionnaire. Generally, a sacrice of a life is other-damaging behavior. Hence, we have introduced a reasonable measure of other-damaging behavior; behavior that disposes payo of an-other person.

Our task measures other-damaging behavior regardless of self-interest. We maintain that our monetary proxy indicates a general taste for a spiteful behavior.

6

At the start of our project, we believed both that men are more spiteful than women and that --contrary to what one would intuitively expect --individuals who indicate greater spitefulness (who are immoral) might tend to commit fewer moral errors, in the utilitarian framework. Surprisingly, we nd that men indicate greater endorsement of utilitarian solutions not because they possess characteristics that most would consider immoral. Our believe about other-damaging preference was supported by ndings in [START_REF] Croson | Gender Dierences in Preferences[END_REF] and Engel (2006). Croson and Gneezy review the literature on gender dierences in other-regarding preferences; research from psychology suggests that women are more sensitive to social cues in determining appropriate behavior. Similarly, in a review of Dictator experiments, Engel (2006) reports that women give signicantly more than men. In our game, other-damaging behavior leads to decisions that are payo eciency-decreasing and payo inequality-increasing (a triple bad). An alternative to our spite game would be the standard Dictator in which other-damaging behavior increases the dictator's payo, and is, by denition, payo-eciency neutral, yet inequality-increasing.

Our experiment is designed as follows: First, we elicit responses to fourteen hypothetical ethical dilemmas. In our paper, we maintain that our questionnaire describes situations that are genuine dilemma --two possibilities neither of which is unambiguously acceptable. We nd consistent and signicant gender dierences in responses to moral questions: men are found to be more prone than women to endorse the act of sacricing one life to save other lives.

Second, we investigate whether gender dierences in moral judgments are robust to individual dierences in anti-social preferences. We apply the tool set of experimental economics; we observe decisions in a game with monetary stakes to measure anti-social preferences. The decision maker is granted a at payo of 10 Euros, and in addition sets the payo for another participant to any amount between 0 and 10 Euros. An amount lower than 10 Euros harms the other person and indicates preferences for spite.

7 Our game provides a simple and 6 An alternative to the spite game is the envy game [START_REF] Bartling | Egalitarianism and Competitiveness[END_REF]), however, the envy game allows for enforcement of an egalitarian outcome, whereas our spite game allows for enforcement of an unequal allocation. We suspect that individuals who are spiteful are individuals who are envious as well.

We did not intend to measure social preference in Fisman et al.'s sense (other versus other, [START_REF] Fisman | Individual Preferences for Giving[END_REF]). One could quite reasonably --be interested in the relationship between trade-os of monetary payments of others and trade-os of lives of others (moral trade-os). In our paper, we maintain that the questionnaires describe situations that are dilemma --two possibilities neither of which is unambiguously acceptable.

7 [START_REF] Charness | Relative Payos and Happiness: An Experimental Study[END_REF] have conducted an experiment with games that are similar to our game; their games distinguish between a motivation to achieve the best for a pair of players or spitefulness. Charness and Grosskopf had been interested in the association between participants self-reported happiness and their concern for relative payos (see Lyubomirsky and Ross (1997) for a social-psychology study into the eect of happiness on the desire for social comparison). Charness and Grosskopf nd little association; most participants disregarded relative payos and instead typically made choices resulting in higher social payo.

Our objective is to classify participants into two types. For richer taxonomies of other-regarding behavior in the laboratory see Fisman, Kariv and Markovits (2007), Murphy, Ackermann, and Handgraaf (2011) and direct way to classify participants in two types: those who engage in anti-social behavior and those who do not. Antisocial behavior is somewhat common in our setting roughly one participant in ve purposefully reduces the other participant's earnings. [START_REF] Bartling | Egalitarianism and Competitiveness[END_REF] We use this indicator variable as a control in regression analysis. We nd that gender is associated with moral judgment even when we control for participants' spitefulness: men are found to be more prone than women to endorse the act of sacricing one life to save many other lives.

Experimental Design

We conducted the sessions at the Experimental Economics Laboratory Paris (LEEP). There were 12 sessions, each with between 11 and 20 participants. From LEEP's database, we recruited participants who had completed LEEP's registration process. We stratied the sampling to ensure balance, with 99 female and 99 male participants. The participants' average age was 24. Most participants had previously taken part in an experiment at LEEP. Roughly four-fths of our participants were still enrolled in university studies. For recruitment, we used the ORSEE software, [START_REF] Greiner | An Online Recruitment System for Economic Experiments[END_REF]. For the sessions, we used the Regate software, Zeilinger (2000). We asked participants to complete two experimental tasks. Specically, participants were asked to both play a game whose outcome determined the participant's monetary gains, and to answer a moral-intuition questionnaire consisting of 14 questions about 14 moral dilemmas. We accounted for potential order eects in two ways. In six sessions, participants rst played the game and then completed the questionnaire. In the other six sessions, the order was reversed. Furthermore, we arranged the order of the presentation of the 14 dilemmas to ensure balance across sessions. 9

At the beginning of each session, instructions were distributed and read aloud. Furthermore, participants were informed that additional instructions would be displayed on their computer screens later on. The instructions and questions, translated from French into English, are available as supplementary material in the appendix. [START_REF] Kerschbamer | The Geometry of Distributional Preferences and a Non-Parametric Identication Approach: The Equality Equivalence Test[END_REF]. Dictator is well-suited for capturing pro-social behavior (sharing with others), but is silent on the reasons for not-sharing-with-others: both selshness and other-damaging preferences predict to the same behavior.

To tease apart selshness from other-damaging preferences, we use the spite game. 9 [START_REF] Petrinovich | Inuence of Wording and Framing Eects on Moral Intuitions[END_REF], [START_REF] Alexander | Analytic Epistemology and Experimental Philosophy[END_REF], and [START_REF] Zamzow | Variations in Ethical Intuitions[END_REF] show that the order of presentations aects moral responses.

Moral-Intuition Questionnaire

We elicit participants' responses to 14 hypothetical moral dilemmas. We are interested in quick, natural replies as we are not concerned with elicitation of explicit moral reasoning.

We have drawn our 14 dilemmas from [START_REF] Bartels | Principled Moral Sentiment and the Flexibility of Moral Judgment and Decision Making[END_REF]. 10 Below we show a typical situation, called Trolley Dilemma, together with the kind of response we elicited.

The Trolley Dilemma:

In the path of a runaway train car are ve railway workmen who will surely be killed unless you, a bystander, do something. You are standing next to a larger stranger on a pedestrian walkway that arches over the tracks. Your body would be too light to stop the train, but if you push the stranger onto the tracks, killing him, his large body will stop the train.

In this situation, would you push the man?

Please, indicate your answer by ticking a box on the scale displayed below (the leftmost box corresponds to the strongest disagreement, the rightmost box corresponds to the highest agreement):

NO -2 -1 -1 2 YES
In the sessions, the dilemmas were presented one by one (see the instructions in the appendix;

note that the Trolley-Dilemma situation above is referred to as Footbridge in the appendix).

Note that the integer -2 signies the strongest disagreement of the sacrice. The integer 2 signies the strongest agreement. We refer to the integers as agreement points.

Experimental Game

Two players, A and B, play a simple game. Player A's payo is 10 Euros. Player A chooses player B's payo by picking an integer between 0 and 10 Euros. Player B makes no decision.

In our sessions, pairs of participants were formed. Each participant made a decision as a Player A. A random draw at the end of each session determined participants' actual roles and actual payos. In addition, each participant received a show-up fee of 5 Euros. 11 We used this procedure to collect data on each participant's game decision. Note that our procedure makes it plain that each participant's choice could aect another participant's payo. Our procedure asks participants to make contingent choices before learning about their actual role in the game [START_REF] Selten | Die Strategiemethode zur Erforschung des Eingeschränkt Rationalen Verhaltens im Rahmen eines Oligopolexperiments[END_REF]).

An alternative procedure could have rst let each participant know her role in the game ex ante, and then ask the participant to makes choices at her actual information set. Let us rst turn to participants' behavior in our incentivized game. Player A is asked to choose player B's payo. We call this choice the transferred amount. Table 1 shows the distribution of transfers; by female participants, by male participants, and by the pooled sample.

Finding 1 (Frequency of Spiteful Choices) Twenty-two percent of the participants chose a transfer less than the maximal transfer.

Support. Finding 2 (No Gender Dierence in Transferred Amounts) We do not reject the null hypothesis that the distribution of transfers is equal for male participants and female participants.

Support. Table 1, row 2 shows the frequency of transfers by female participants. Table 1, row 3 shows the frequency for male participants. A Wilcoxon rank-sum test of no dierence of the distributions shows p = 0.347.

Next, we turn to moral judgment. Table 2 shows the score for each of the 14 items of the moral-dilemma questionnaire. The panel to the left shows the statistics sorted by gender, the panel in the middle shows the statistics sorted by the transferred amount, and the panel to the right shows the statistics for pooled sample.

Note that the moral situations are dierent in various dimensions.

12 Now, the situations have something in common, and our questionnaire is designed to measure this common variable. The internal consistency of the questionnaire is very high; Cronbach's α is around 0.8 for the 14 situations (see the nal row of to dierent situations show that the questionnaire is well suited for measuring a commonality the degree of endorsement of the utilitarian solution. Note that the commonality does allow for reasonable discussion of moral principles utilitarianism versus ontology. Furthermore, after partitioning the sample by gender and transferred amount, the high internal consistency of the questionnaire is upheld. In table 2 (nal row), we now report Cronbach's α for male (n = 99) and female participants (n = 99), and for other-damaging participants (n = 43) and participants who are not other-damaging (n = 155). These results suggest that moral judgment is robust across fourteen situations in the four subgroups. Hence, we are justied to use the average score as a dependent variable in our regression analysis.

Finding 3 (Gender Dierence in Moral Judgment)

We reject the null hypothesis that the distribution of moral intuitions is equal for men and women.

Support. We do not reject the null hypothesis that the distribution of moral intuitions is equal for spiteful and non-spiteful players.

Support. Table 2, columns 5 and 6 show the scores of participants who act pro-socially as Player A in the experimental game (i.e., the transferred amount equals 10), and those who act anti-socially (by transferring less than 10). Among 14 items, we nd no instance for which the dierence in moral judgments between these two groups is signicant at the 5% level, and one instance in which it is weakly signicant at the 10% level. The p values from two-sided t-tests are shown in column 7. We conclude that the overall average scores are not statistically dierent at the conventional levels.

We found that the individual average score is a reliable measure of one's endorsement for utilitarian solution. Now, we explain the score's variation using regression models. The sets of explanatory variables include the two main characteristics of interest; gender and behavior in the game.

Table 3 shows 15 regression results. For 14 regressions, the dependent variable is a participant's points of agreement. Each of the 14 regressions corresponds to a situation.

For the 15th regression, the dependent variable is participants' overall average points of agreement. The key explanatory variable is an indicator variable 1[M ALE] that is 1 for males and 0 for females (β 3 ). The controls are 1[AM OU N T < 10], that is 1 if the participant chose to transfer less than 10 and 0 otherwise (β 1 ), 1[AM OU N T < 10] × AM OU N T (β 2 ), and 1[GAM E F IRST ] if the game was followed by the questionnaire, and 0 otherwise (β 4 ).

Finding 5 (Gender Eect on Intuitions)

We nd a gender eect in moral intuitions even when we control for the transferred amount.

Support. Table 3 shows the regression output for the 14 individual regressions in a separate panel. We present the estimated coecients for the male indicator variable and the corresponding p value. In 8 out of 14 situations, the male indicator variable is signicant at the 5% level. Table 3 also shows the overall regression in the panel to the lower right: the male indicator variable is highly signicant at the 1% level.

In the average-points-of-agreement regression, the controls [AM OU N T < 10] and 1[AM OU N T < 10] × AM OU N T are individually and jointly insignicant. In the Plane Crash regression, the controls [AM OU N T < 10] and 1[AM OU N T < 10] × AM OU N T are individually and jointly signicant. 14 In the other 13 individual regressions, the controls [AM OU N T < 10] level. In the supplementary material, we show results from an ordered probit regression. We nd a gender eect in moral intuitions even when we control for the transferred amount as well. [START_REF] Charness | The Dark Side of Competition for Status[END_REF] 4

Conclusions

Our contribution is threefold. First, we conducted a questionnaire that allows us to measure consistently moral judgment in fourteen well-studied one-life-for-ve-lives situations in which inicting harm on one person allows many others to escape suering. We demonstrated systematic gender dierences in moral judgment: men are more supportive of the sacrice than women. Second, we investigated a transfer game in which an advantaged player simply decides the payo of the disadvantaged player while her payment is held constant. We nd that a fth of the participants transfer less than the maximum, and that men and women behave spitefully in equal proportion. Third, we combined our data on moral judgment with our data on transfer decisions. We nd robustly across several dilemmas, and highly signicantly overall that women approve of a sacrice less than men even when we control for individual dierences in social preferences in our regression analysis.

We elicited participants' moral judgment of an action, not the actual moral action. We emphasize that both aspects judgment of an action and the action itself are important.

Consider, for instance, a question of judgment: Which life-or-death decisions does our society want to make?. On the contrary, consider now the question: Who do we want to make those decisions?. For instance, society may have to decide on who serves in our security forces that tackle terrorist incidences, and in which way do we want our forces to tackle those threats to our lives. We believe that more evidence is needed to understand the relationship between moral judgment of an action and actual moral behavior. Our paper is a step in this direction.

Appendix: Design and Instructions

In each session, participants were asked to answer a standard questionnaire. We used the questionaire to elicit demographic information. In addition, participants were required both to play an experimental game and to answer a moral-intuition questionnaire. Below we present the paper instructions (subsection 1), describe the instructions displayed on the participants' computer screens (subsection 2), and present the moral-intuition questionnaire (subsection 3). Sentences in brackets were not part of the instructions but rather descriptions of what happened.

Instructions On Paper

You are taking part in an experiment in which you can earn money. Your gains may depend on the decision made by another participant. Before we begin we would like you to answer a few standard questions concerning your age, education, profession, etc.. These questions will help us to get to learn something about your characteristics. Your identity and your monetary gains will remain condential and anonymous.

[Participants lled out the standard questionnaire.]

Thank you for answering the questions.

What happens in the Session

The experiment consists of two separate parts. In Part 1 your payment in the session will be determined. In Part 2 you will be asked to answer questions that will allow us to learn more about you. Further instructions will be displayed on your screen before the beginning of each part.

Payment of your earnings

Your total payment will the payo you earn in Part 1 and a bonus of 5 Euros for completing the session. Payments are made individually and in cash.

You are not allowed to talk during the experiment. Participants who violate this rule will be excluded from the experiment and payments. It is important that you perfectly understand the rules of this experiment. Should you have any questions, please raise your hand.

Thank you again for your participation.

5.2

Computer Screen

[Experimental Game: Information on the First Screen]

In this part of the experiment, your additional payment will be determined. The game has two players: player A and player B. Only player A makes a decision, and this decision aects player B's payo only. You will be paired randomly with another participant. You will then be asked about the decision you would make as player A. Finally, at the end of the experiment, a random draw will determine your actual role in the pair. If you are player A, your decision will determine the other group member's payo. If you are player B, your payo will be determined by player A.

[Experimental Game Information on the Second Screen]

Moral-Intuitions Questionnaire

In this part of the session, we ask you to answer a few questions. The answers will enable us to learn about some of your personal characteristics. We remind you that we are not able to link your answers with your identity.

[Participants used a computer mouse to tick the appropriate box on a scale of-2, -1, 1, 2.

The leftmost box represents the strongest disagreement and the rightmost box corresponds to the highest agreement.

Submarine

You are the captain of a small military submarine traveling underneath a large iceberg. An on-board explosion has dramatically decreased the oxygen supply and has injured a member of the crew. He may die from his injuries. The remaining oxygen is not sucient for the entire six-man crew to make it to the surface. If you shoot the injured crew member, there will be just enough oxygen for everyone else to survive.

In this situation, would you shoot the crew member?

Trespassers

You and a group of friends are backpacking, and while crossing a rocky plain in the Guatemalan highlands, you inadvertently camp on a local clan's burial ground. The leader of the clan says that his clan's laws command him to kill all six of you as a sacrice to the gods, but that if you kill one of your own, the gods will be appeased, and the rest will be let go.

In this situation, would you kill one of your friends?

Hostages

You are traveling with ve other peace advocates in a war-torn country when your group is taken hostage by a group of terrorists. After a week, the terrorists' demands have not been met, and they oer you a choice: either they will kill all of you, or if you execute one of your fellow hostages, you and the others will be free to go.

In this situation, would you execute one of your fellow hostages?

Bystander

In the path of a runaway train car are ve railway workmen who will surely be killed unless you, a bystander, do something. If you ip a switch, the train will be diverted onto another track, where it will kill a single railway workman.

In this situation, would you ip the switch?

Life Raft

You are on a small ship, a re breaks out, and the ship has to be abandoned. Because your tiny life raft is carrying more than its capacity, it is sitting dangerously low in the water.

The seas get rough and the raft begins to ll with water. Unless you do something, all six of you will drown. There is an injured person on board who may die either way. If you throw him overboard, everyone else will be saved.

In this situation, would you throw him overboard?

Plane Crash

Your plane has crashed in the Himalayas. The only survivors are you, some other men, and a young boy. The six of you travel for days, battling extreme cold and wind. Your only chance of survival is to make it to a village a few days away. The boy cannot move very quickly.

Without food, you and the other men will surely die. One of the men suggests killing the boy and eating his remains over the next few days.

In this situation, would you sacrice the boy?

Prisoners of War

You and some other soldiers were captured. After a year in a prison camp, your group tried to escape but was caught. The warden has decided to hang your group in front of the other prisoners of war. At the gallows, he releases the noose from your neck and announces that if you pull the chair from underneath one man in your group, the remaining ve will be set free; otherwise you all die. He means what he says.

In this situation, would you remove the chair?

Fumes

You are the late-night watchman in a hospital where an accident has occurred in one of the on-site testing labs, and now there are deadly fumes rising up through the hospital's ventilation system. The fumes are headed to a certain area where there are ve patients who will surely die. If you ip a switch, the ventilation system will cause the fumes to bypass this room and enter a room containing a single patient, killing him.

In this situation, would you ip the switch?

Spelunkers

You and ve others are exploring a seashore cave. A rock falls and blocks your exit. The tide is rising. You spot a hole elsewhere and let a large man in your group out rst. He gets stuck, and unless you get out soon, everyone but this man (whose head is sticking out of the cave) will drown. You have a stick of dynamite that will not move the rock, but will blast the man out of the hole. He does not want to die; neither do you or the others.

In this situation, would you blast him out?

Soldiers

You are leading a group of soldiers returning from a completed mission in enemy territory when one of your men steps in a trap. He is injured, and the trap is connected to a device that alerts the enemy to your presence. If the enemy nds your group, all six of you will die.

If you leave him behind, he will be killed, but the rest of the group will escape safely.

In this situation, would you leave him behind?

Surgery

You are a surgeon with a number of patients. Five of them need organ transplants. Each of them needs a dierent organ or they will surely die. You have another patient who is healthy and would be an ideal organ donor for the others. If you transplant his organs (against his will) into the bodies of the other patients, they will live but he will die.

In this situation, would you perform this transplant?

Derailment

In the path of a runaway train car are ve railway workmen who will surely be killed unless you, a bystander, do something. If you ip a switch, the train will be diverted onto a set of tracks in need of repair. The train will be derailed and go down a hill, across a road, and into a man's yard. The owner, sleeping in his hammock, will be killed.

In this situation, would you ip the switch?

Footbridge

In the path of a runaway train car are ve railway workmen who will surely be killed unless you, a bystander, do something. You are standing next to a larger stranger on a pedestrian walkway that arches over the tracks. Your body would be too light to stop the train, but if you push the stranger onto the tracks, killing him, his large body will stop the train.

In this situation, would you push the man?

8

  Our estimate of the proportion of spiteful types echoes the ndings by[START_REF] Levine | Modeling Altruism and Spitefulness in Experiments[END_REF] andCharness, Masclet, and Villeval (2014). Levine estimates that about 20% of participants engage in spiteful behavior. Levine species a model in which players have a utility function that weights other player's payo with a parameter α; positive values of α show altruism and negative values show spitefulness. In addition, players could tend to be more altruistic to an opponent who is more altruistic toward them. Levine looks at data from ultimatum (Roth et al. (1991), competitive auction (Roth et al (1991), centipede (McKelvey and Palfrey (1992)), and public goods contribution game (Isaac and Walker (1988)). Interestingly, Levine (p. 616) predicts behavior for our game accurately. Zizzo and Oswald (2001) use a similar game as well. They nd a larger fraction of spiteful behavior; participants pay to 'burn' the money of the bigger earners. Their result suggests that one could manipulate the amount of spitefulness if the other player has a larger endowment than the decision-maker.

11 10

 11 Bartels drew his dilemmas from the psychology literature. The references for the dilemmas are: Subma- rine (Greene et al. 2001), Trespassers (Greene et al. 2001), Hostages (Greene et al. 2001), Bystander (Foot 1967), Life Raft (Regan 1983), Plane Crash (Marshall 1993, Greene et al. 2001), Prisoners of War (Baron 1992), Fumes (Thompson 1986), Spelunkers (http://news.bbc.co.uk/2/hi/uk_news/magazine/4954856.stm), Surgery (Foot 1967), Derailment (Unger 1996), Footbridge (Thompson 1985), and Baby (Alda et al. 1983, Greene et al. 2001).

Table 1 :

 1 Distribution of Transfers in the Experimental Game

	Transferred Amount (in Euros)	0	1	2	3	4	5	6	7	8	9	10	Σ
	Number of Choices by Females	0	1	0	1	1	7	2	1	8	4	74	99
	Number of Choices by Males	0	1	0	1	1	11	0	1	1	2	81	99
	Total Number of Choices	0	2	0	2	2	18	2	2	9	6	155	198
	3 Results

The literature shows that both methods yield similar results with simple distributional games that involve very few contingent choices (for Dictator see

[START_REF] Cason | Social Inuence in the Sequential Dictator Game[END_REF]

and for a Solidarity Game see

[START_REF] Büchner | Self-centered and Other-regarding Behavior in the Solidarity Game[END_REF]

. For a survey of further experimental evidence on the eect of the two methods see

[START_REF] Brandts | The Strategy Versus the Direct-Response Method: A First Survey of Experimental Comparisons[END_REF]

.

Table 1

 1

, row 4 shows the overall frequency of transfers. Most participants (155) selected the maximal transfer, 10. A sizable fraction of the participants transferred lower amounts; the most frequent among those were 5 (18 participants), 8 (9 participants), and 9 (6 participants).

Table 2 )

 2 13 . The high correlations between the response

	Type of	Gender		Transferred Amount		Pooled
	Dilemma	FEMALE	MALE	p value AMOUNT=10 AMOUNT<10 p value
	Observations Submarine Trespassers Hostages Bystander Life Raft Plane Crash Prisoners of War Fumes Spelunkers Soldiers Surgery Derailment Footbridge Baby	99 -0.071 -1.222 -0.606 0.394 0.222 -1.586 -0.010 0.121 -0.596 0.222 -1.818 -0.222 -1.606 -0.869	99 0.535 -0.707 -0.030 0.828 1.010 -1.404 0.202 0.636 0.253 0.485 -1.455 0.061 -1.576 -0.172	0.004 a 0.009 a 0.012 b 0.036 b 0.001 a 0.198 0.350 0.010 a 0.001 a 0.243 0.003 a 0.188 0.818 0.001 a	155 0.271 -0.981 -0.342 0.535 0.568 -1.548 0.077 0.316 -0.213 0.316 -1.697 -0.058 -1.594 -0.548	43 0.093 -0.907 -0.233 0.884 0.791 -1.302 0.163 0.605 -0.023 0.488 -1.419 -0.163 -1.581 -0.419	0.491 0.760 0.697 0.168 0.385 0.150 0.757 0.275 0.471 0.528 0.062 0.688 0.939 0.619	198 0.232 -0.965 -0.318 0.611 0.616 -1.495 0.096 0.379 -0.172 0.354 -1.636 -0.081 -1.591 -0.520
	Overall	-0.546	-0.095	0.001 a	-0.350	-0.216	0.315	-0.321
				Internal Consistency
	Cronbach's α	0.765	0.829		0.824	0.791		0.818

Table 2 :

 2

Points of agreement for sacrice in the moral-judgement questionnaire. Range of agreement points -2 (strongest disagreement), -1, 1, 2 (strongest agreement). p values from Wilcoxon rank-sum and two-sided t-tests. Superscript a denotes p < 0.01, and superscript b denotes p < 0.05.

Table 2

 2 , column 4 shows the p values of the test of no dierence in the distribution of agreement points of female participants and male participants for each of the 14 situations. Male participants' declared support for the sacrice diers from that of the female participants. In 9 out of 14 situations, the dierence is signicant at the 5% level with a t-test. Table2, third to nal row shows the p values of the test of no dierence in the distribution of overall scores of female and male participants. Male participants' average score is not equal to female participants' average score. The two-sided t-test shows a highly signicant dierence (p < 0.001).

	Finding 4 (No Dierence in Moral Judgment Between Spiteful and Non-
	Spiteful Players)

Table 3 :

 3 14 The estimated marginal eect is β1 + β2 • AM OU N T = 1.499 + (-2.06) • AM OU N T . For instance, if est. Regression results; Dependent variable is points of agreement, one for each of the 14 situations. For the model in the bottom right panel, the dependent variable is average points of agreement, across the 14 situations. Superscript a denotes p < 0.01, superscript b

	Type of Dilemma	p Submarine	est. Trespassers p	est. Hostages p	est. Bystanders p
	Intercept	β 0 0.226 0.227 -1.252 a 0.000 -0.691 a	0.001	0.292	0.120
	1[AMOUNT<10] β 1 0.606 0.378 0.674 0.304 0.009	0.991	-0.177	0.797
	× AMOUNT β 2 -0.121 0.260 -0.091 0.371 0.027	0.819	0.096	0.371
	1[MALE]	β 3 0.585 a 0.005 0.501 b 0.012 0.592 b	0.011	0.486	b	0.021
	1[GAME FIRST] β 4 -0.532 0.011 0.019 0.925 0.080	0.725	-0.022	0.916
	H 0 : β 1 = β 2 = 0	0.477	0.580		0.806		0.194
	R 2	0.081	0.040	0.035		0.039
	Type Of Dilemma	Life Raft	Plane Crash Prisoners Of War	Fumes
	Intercept	β 0 0.237 0.203 -1.685 a 0.000 -0.054	0.794	0.016	0.935
	1[AMOUNT<10] β 1 0.635 0.353 1.499 a 0.001 -0.075	0.922	0.625	0.385
	× AMOUNT β 2 -0.055 0.606 -0.206 a 0.004 0.031	0.797	-0.047	0.675
	1[MALE]	β 3 0.802 a 0.000 0.147 0.294 0.226	0.328	0.526	0.017
	1[GAME FIRST] β 4 -0.180 0.380 0.122 0.379 0.027	0.906	0.051	0.812
	H 0 : β 1 = β 2 = 0	0.410	0.012		0.897		0.388
	R 2	0.083	0.064	0.006		0.038
	Type Of Dilemma	Spelunkers	Soldiers	Surgery	Derailment
	Intercept	β 0 -0.776 a 0.000 0.298 0.145 -1.864 a	0.000	-0.311	0.110
	1[AMOUNT<10] β 1 0.276 0.692 -0.050 0.947 0.687 c	0.087	1.002	0.161
	× AMOUNT β 2 0.001 0.996 0.042 0.719 -0.062	0.323	-0.181	0.105
	1[MALE]	β 3 0.861 a 0.000 0.296 0.195 0.373 a	0.002	0.225	0.299
	1[GAME FIRST] β 4 0.230 0.272 -0.278 0.218 -0.056	0.643	0.276	0.197
	H 0 : β 1 = β 2 = 0	0.546	0.715		0.059		0.260
	R 2 Type Of Dilemma	0.090 Footbridge	0.018 Baby	0.073		0.031 Average Score over Dilemma
	Intercept	β 0 -1.638 a 0.000 -0.991 a 0.000			-0.585	a	0.000
	1[AMOUNT<10] β 1 0.169 0.702 0.716 0.307			0.471	0.180
	× AMOUNT β 2 -0.026 0.709 -0.086 0.432			-0.048	0.376
	1[Male]	β 3 0.023 0.864 0.685 a 0.001			0.452	a	0.000
	1[GAME FIRST] β 4 0.067 0.614 0.172 0.412			-0.002	0.988
	H 0 : β 1 = β 2 = 0	0.928	0.535				0.247
	R 2	0.002	0.063			0.099

denotes p < 0.05, and superscript c denotes p < 0.10. N = 198. and 1[AM OU N T < 10] × AM OU N T are individually and jointly insignicant at the 5%

Table 4 :

 4 14. BabyEnemy soldiers have taken over your village and will kill all remaining civilians. You and ve others are hiding in the cellar of a large house. Soldiers have come to search the house for valuables. A baby in your group begins to cry. So, you cover her mouth, but she cannot breathe. If you remove your hand, the baby can breathe, but her crying will summon the soldiers who will kill everyone in the cellar.

	In this situation, would you smother the baby?
	[Participants were thanked for their participation and paid in private.]

0 : β 1 = β 2 = 0 Ordered Logit regression results; Dependent variable is points of agreement, one for each of the 14 situations. For the model in the bottom right panel, the dependent variable is average points of agreement, across the 14 situations. Superscript a denotes p < 0.01, superscript b denotes p < 0.05, and superscript c denotes p < 0.10. N = 198.

This school of thought is known as consequentialism. It says that the moral status of an action should be determined based on the outcome it produces; other features of the action, like the actor's intentions, and the circumstances in which they are undertaken, are irrelevant. Utilitarianism is a version of consequentalism. It combines consequential-ism with welfarism. Welfarism holds that the goodness of an outcome is a matter of the amount of individual well-being, counting everyone equally. Hence, utilitarianism is the view that an act is right if and only if it leads to the greatest total amount of well-being. See, for instance,[START_REF] Harsanyi | Essays on Ethics, Social behavior, and Scientic Explanation[END_REF].

Recently, some experimenters have investigated incentivized moral dilemmas in which people's decisions bear real material consequences. See Hsu, Anen, and Quartz (2008), Gold, Colman, and Pulford (2014) and[START_REF] Gold | Do as I Say, Don't Do as I Do: Dierences in Moral Judgments Do not Translate Into Dierences in Decisions in Real-life Trolley Problems[END_REF]. For instance, Gold, Colman, and Pulford (2014) look at a version of a moral dilemma in which the harm is a small economic loss. The authors nd somewhat of a dierence between actions and judgements, yet conclude that nothing denitive can be said about the scope and causes of observed dierence. Regrettably, the authors look merely at a tiny number of scenarios. Furthermore, the authors do not report on measures of correlation between responses.

The task in the experiment was to distribute meals among poor African kids through a charity. Each child was given an initial endowment of twenty-four meals. The policy decision was either take away plenty from one child fteen meals less then plenty from two children thirteen meals or ve meals. The caveat of the study is the very small sample size with only 26 participants, 17 women and 9 men.

[START_REF] Adleberg | Do Men and Women have Dierent Philosophical Intuitions? Further Data[END_REF] review studies reporting a variety of methodologies for tests of gender dierences in philosophical judgements.

We thank a referee for pointing out that the moral situations are dierent in the dimensions (a) life at stake, (b) volunteer opportunity, and (c) responsibility.

[START_REF] Tavakol | Making sense of Cronbach's alpha[END_REF] describe internal consistency as the extent to which all the items in a test measure the same concept. Internal consistency is connected to the inter-relatedness of the items within the test (see Tavakol and Dennick, page 53). Commonly, values of range from 0.70 to 0.95 are acceptable (see Tavakol and Dennick, page 54).

In the Plane-Crash regression, the controls [AM OU N T < 10] and 1[AM OU N T < 10] × AM OU N T are individually and jointly signicant. We argue above that our questionnaire measures a common moral variable. Hence, an explanation about dierences between situations could be ad hoc, and capture natural sample variation. If were to explore peculiarities of this situation, one could argue that PLANE-CRASH is an extreme situation in which the utilitarian solution asks for killing of a child. It may be that most people are extremely averse to killing a child, and hence, our moral measure (the triple bad) may very well be a good predictor for such extreme behavior. Note also while our results show that people are averse to killing a child, in this instance, women are not more averse than men (see Table2, plane crash, average score for FEMALE -1.4 and for MALE -1.6). The result seems to contradict a stereotype; women supposedly have preference for caring for and protecting someone while they are growing (nurture).

* The research has been supported by the French National Research Agency (ANR), through the program Investissements d'Avenir (ANR-10LABX_93-01). The research has been was performed within the framework of LABEX CORTEX (ANR-11-LABX-0042) of Universite de Lyon, within the program Investissements d'Avenir (ANR-11-IDEX-007) run by the French National Research Agency (ANR). Maxim Frolov, Ivan Ouss and Remi Yin assisted with the experimental sessions. We thank Crete, at the GATE CNRS Laboratory, and at the French Experimental Economics Association Meeting in Paris for valuable comments. Adam Zylbersztejn is grateful to the University of Lyon

Supplementary Material

1. In the supplement, we show a second set of regression results. In the ordered logit regression, we revisit our original set of explanatory variables; indicator variable 1[M ALE] that is 1 for males and 0 for females (β 3 ), 1[AM OU N T < 10], that is 1 if the participant chose to transfer less than 10 and 0 otherwise (β 1 ), 1[AM OU N T < 10] × AM OU N T (β 2 ), and 1[GAM E F IRST ] if the game was followed by the questionnaire, and 0 otherwise (β 4 ). The analysis supports Finding 5 (Gender Eect on Intuitions). We nd a gender eect in moral intuitions even when we control for the transferred amount. In 9 out of 14 situations, the male indicator variable is signicant at the 5% level.