An increasing number of studies exploit the occurrence of unexpected events during the fieldwork of public opinion surveys to estimate causal effects. In this paper we discuss the use of this identification strategy based on unforeseen and salient events that split the sample of respondents into treatment and control groups: the Unexpected Event during Surveys Design (UESD). In particular we focus on the assumptions under which unexpected events can be exploited to estimate causal effects and we discuss potential threats to identification, paying especial attention to the observable and testable implications of these assumptions. We propose a series of best practices in the form of various estimation strategies and robustness checks that can be used to lend credibility to the causal estimates. Drawing on data from the European Social Survey we illustrate the discussion of this method with an original study of the impact of the Charlie Hebdo terrorist attacks (Paris, 01/07/2015) on French citizens' satisfaction with their national government.

Pilot trainees’ ability to manage unexpected events is crucial for aviation safety, yet the impact of event urgency and flight scenario familiarity on pilot performance remains under-explored. This study investigates how different urgency levels of unexpected events influence pilot trainees’ flight performance, heart rate, and anxiety in both familiar (single-engine) and less familiar (twin-engine) flight scenarios. Two controlled experiments were conducted using flight simulators: Experiment 1 involved 27 pilot trainees operating a Cessna 172 single-engine simulator under low-urgency and high-urgency conditions, while Experiment 2 involved 25 pilot trainees using a FTD D40/D42 twin-engine simulator, introducing an additional no-event baseline. In the single-engine flight scenario, high-urgency unexpected events significantly impaired pilot trainees’ performance (Cohen’d = 0.454) and increased anxiety (ηp2 = 0.229). In the twin-engine flight scenario, high-urgency unexpected events significantly impaired flight performance (MEI increased, ηp2 = 0.737), elevated heart rate (ηp2 = 0.516), and increased anxiety levels (ηp2 = 0.442) compared to low-urgency events, which had minimal effects and, in some cases, improved pilot trainees focus. Additionally, pilot trainees performed better and exhibited lower anxiety in familiar scenarios, suggesting that task familiarity mitigates the negative impact of high-urgency unexpected events. These findings highlight the importance of incorporating urgency-based training scenarios and cross-aircraft training to enhance pilot trainees’ adaptive responses to unexpected events, ultimately improving flight safety.

This article presents new empirical evidence about the impact of Jihadist terrorist attacks on far right preferences using the ‘unexpected event during survey’ research design. This strategy allows us to match individual-level data from the European Social Survey (ESS) to data on Jihadist terrorist attacks to compare respondents’ party preferences before and after a terrorist attack during the same survey period in the Netherlands, Sweden, France and Germany. We theorise and test three distinct hypotheses about how different combinations of attitudinal changes including out-group prejudice and trust in institutions impact on far right preferences. We find no statistically significant effects. Analyses of the two indirect mechanisms- i.e., prejudice and trust- yield mixed results consistent with the null effect on far right party preferences. By showing that terrorist attacks are unlikely to decisively change party support despite attracting significant public attention and affecting political attitudes, our results challenge the argument that Jihadist terrorism necessarily benefits the far-right and highlight the importance of null effects for overcoming confirmation bias in the study of voting behaviour.

Across the United States, roughly 50 percent of employees reported that they faced surprise hospital bills due to unexpected serious health events, accidents, or hospitalizations in both 2020 and 2021. In 2021, 88 percent of U.S. employees have faced unexpected costs (most often medical-related), compared to 92 percent in 2020. This statistic shows the share of employees facing unexpected costs from serious health events, accidents, or hospitalizations in the U.S. in 2020 and 2021.

This package containts replication instructions for the analysis in “Judicial Decisions, Backlash and Secessionism: The Spanish Constitutional Court and Catalonia” by Agustin Casas, Federico Curci, and Antoni-Italo de Moragas in the Economic Journal. Please begin with the detailed Readme file and let us know if you have doubts.

The paper study the effects of judicial decisions on sensitive issues on political attitudes. In 2010, the Spanish Constitutional Court
partially overruled the new Catalan Constitution–the Estatut–that granted further decentralization. The main result is that the ruling increased support for independence by 5 percentage points. Please take a look at the paper to see the mechanisms and additional results.

The data represent the acceleration, angular velocity, and strain at two locations on the structure under four testing scenarios including numerical, impact, ground motion, and water flume.

While a number of high-level figures around the world have been prosecuted and even jailed for corruption in recent years, we know little about how such anticorruption efforts shape public opinion and patterns of political engagement. To address this question, we examine evidence from Argentina and Costa Rica involving the unprecedented sentencing of two former Presidents on corruption charges. Exploiting the coincidence in timing between these cases and fieldwork on nationally representative surveys, we find that citizens interviewed in the aftermath of these events expressed lower trust in institutions and were less willing to vote or join in collective demonstrations. Overall, these findings suggest that high-profile efforts to punish corrupt actors may have similar effects as political scandals in shaping citizens' relationship to the political system.

The expectation that voters behave rationally has been challenged through studies suggesting that ‘irrelevant events’ like natural disasters and sports results change voting behavior. We test the effect of irrelevant events by matching candidate-level election results from Irish general (1922–2020) and local elections (1942–2019) with games in the Gaelic football and hurling championships, the most popular sports in Ireland. Although Irish citizens care deeply about sports, we fail to find any relationship between match results and support for incumbents or politicians of government parties. These findings hold when applying an ‘unexpected event during survey design’ to two representative surveys. Our results contribute to the literature on political accountability and point to conditional effects of irrelevant events.

Excess of deaths for the Brazilian dataset.

Excess of deaths for the Spanish dataset.

The brain constantly generates predictions about the environment to guide action. Unexpected events lead to surprise and can necessitate the modification of ongoing behavior. Surprise can occur for any sensory domain, but it is not clear how these separate surprise signals are integrated to affect motor output. By applying a trial-to-trial Bayesian surprise model to human electroencephalography data recorded during a cross-modal oddball task, we tested whether there are separate predictive models for different sensory modalities (visual, auditory), or whether expectations are integrated across modalities such that surprise in one modality decreases surprise for a subsequent unexpected event in the other modality. We found that while surprise was represented in a common frontal signature across sensory modalities (the fronto-central P3 event-related potential), the single-trial amplitudes of this signature more closely conformed to a model with separate surprise terms for each sensory domain. We then investigated whether surprise-related fronto-central P3 activity indexes the rapid inhibitory control of ongoing behavior after surprise, as suggested by recent theories. Confirming this prediction, the fronto-central P3 amplitude after both auditory and visual unexpected events was highly correlated with the fronto-central P3 found after stop-signals (measured in a separate stop-signal task). Moreover, surprise-related and stopping-related activity loaded onto the same component in a cross-task independent components analysis. Together, these findings suggest that medial frontal cortex maintains separate predictive models for different sensory domains, but engages a common mechanism for inhibitory control of behavior regardless of the source of surprise.

Accuracy measures for the models over the Brazilian data from January 2015 to December 2019.

Dataset description

This dataset contains fMRI data from adults from one paper, with two experiments in it:

Liu, S., Lydic, K., Mei, L., & Saxe, R. (in press, Imaging Neuroscience). Violations of physical and psychological expectations in the human adult brain. Preprint: https://doi.org/10.31234/osf.io/54x6b

All subjects who contributed data to this repository consented explicitly to share their de-faced brain images publicly on OpenNeuro. Experiment 1 has 16 subjects who gave consent to share (17 total), and Experiment 2 has 29 subjects who gave consent to share (32 total). Experiment 1 subjects have subject IDs starting with "SAXNES*", and Experiment 2 subjects have subject IDs starting with "SAXNES2*".

• code/ contains contrast files used in published work
• sub-SAXNES*/ contains anatomical and functional images, and event files for each functional image. Event files contains the onset, duration, and condition labels
• CHANGES will be logged in this file

Tasks

• VOE (Experiment 1 version): Novel task using hand-crafted stimuli from developmental psychology, showing violations of object solidity and support, and violations of goal-directed and efficient action. There were only 4 sets of stimuli in this experiment, that repeated across runs. Shown in mini-blocks of familization + two test events.
• VOE (Experiment 2 version): Novel task including all stimuli from Experiment 1 except for support, showing violations of object permanence and continuity (from ADEPT dataset; Smith et al. 2019) and violations of goal-directed and efficient action (from AGENT dataset; Shu et al. 2021). Shown in pairs of familiarization + one test event (either expected or unexpected). All subjects saw one set of stimuli in runs 1-2, and a second set of stimuli in runs 3-4. If someone saw an expected outcome from a scenario in one run, they saw the unexpected outcome from the same scenario in the other run.
• DOTS (2 runs, both Exp 1-2): Task contrasting social and physical interaction (Fischer et al. 2016, PNAS). Designed to localize regions like the STS and SMG.
• Motion: Task contrasting coherent and incoherent motion (Robertson et al. 2014, Brain). Designed to localize area MT.
• spWM: Task contrasting a hard vs easy spatial working memory task (Fedorenko et al., 2013, PNAS). Designed to localize multiple demand regions.

There are (anonymized) event files associated with each run, subject and task, and contrast files.

Event files

All event files, for all tasks, have the following cols: onset_time, duration, trial_type and response_time. Below are notes about subject-specific event files.

• sub-SAXNES2s001: The original MotionLoc outputs list the first block, 10s into the experiment, as the first event. This was preceded by a 10s fixation. For s001, prior to updating the script to reflect this 10s lag, we had to do some estimation - we saw that on average, each block was 11.8s but there was usually a .05s delay, such that each block started ~11.85s after the previous one. Thus we calculated start times as 11.85 after the previous block. For the rest of the subjects, the outputs were not manipulated - we just added an event to the start of the run.
• sub-SAXNES2s013: no event files for DOTS run2; event files use approximate timings instead based on inferred information about block order
• sub-SAXNES2s018 (excluded from sample): no event files, because this subject stopped participating without having contributed a complete, low-motion run, for which it was clear they were following the instructions for the task
• sub-SAXNES2s019: no time to do run2 of DOTS or Motion, so only 1 run for those two
• sub-SAXNES2s023, the event files from spWM run 1 did not save during scanning. We use timings from the default settings of condition 1 but we do not have trial-level data from this person.

For the DOTS and VOE event files from Experiment 1, we have the additional columns:

• experimentName ('DotsSocPhys' or 'VOESocPhys')
• correct: at the end of the trial, subs made a response. In DOTS, they indicated whether the dot that disappeared reappeared at a plausible location. In VOE, they pressed a button when the fixation appeared as a cross rather than a plus sign. This col indicates whether the sub responded correctly (1/0)
• stim_path: path to the stimuli, relative to the root BIDS directory, i.e. BIDS/stimuli/DOTS/xxxx

For the DOTS event files from Experiment 2, we have the additional columns:

• participant: redundant with the file name
• experiment_name: name of the task, redundant with file name
• block_order: which order the dots trials happened in (1 or 2)
• prop_correct: the proportion of correct responses over the entire run

For the Motion event files from Experiment 2, we have the additional columns:

• experiment_name: name of the task, redundant with file name
• block_order: which order the dots trials happened in (1 or 2)
• event: the index of the current event (0-22)

For the spWM event files from Experiment 2, we have the additional columns:

• experiment_name: name of the task, redundant with file name
• participant: redundant with the file name
• block_order: which order the dots trials happened in (1 or 2)
• run_accuracy_hard: the proportion of correct responses for the hard trials in this run
• run_accuracy_easy: the proportion of correct responses for the easy trials in this run

For the VOE event files from Experiment 2, we have the additional columns:

• trial_type_specific: identifies trials at one more level of granularity, with respect to domain task and event (e.g. psychology_efficiency_unexp)
• trial_type_morespecific: similar to trial_type_specific but includes information about domain task scenario and event (e.g. psychology_efficiency_trial-15-over_unexp)
• experiment_name: name of the task, redundant with file name
• participant: redundant with the file name
• correct: whether the response for this trial was correct (1, or 0)
• time_elapsed: how much time as elapsed by the end of this trial, in ms
• trial_n: the index of the current event
• correct_answer: what the correct answer was for the attention check (yes or no)
• subject_correct: whether the subject in fact was correct in their response
• event: fam, expected, or unexpected
• identical_tests: were the test events identical, for this trial?
• stim_ID: numerical string picking out each unique stimulus
• scenario_string: string identifying each scenario within each task
• domain: physics, psychology (psychology-action), both (psychology-environment)
• task: solidity, permanence, goal, efficiency, infer-constraints, or agent-solidity
• prop_correct:the proportion of correct responses over the entire run
• stim_path: path to the stimuli, relative to the root BIDS directory, i.e. BIDS/stimuli/VOE/xxxx

Associated Links

• OSF: https://osf.io/sa7jy/

The Sartorius Scale Monitor software has three goals. First, the software communicates with Sartorius scales that support the SBI protocol to query and convert the scale values in real-time, monitoring the calculated values and triggering an alarm in case of an unexpected event. The second goal is to provide the user with a web-based interface that provides alarm settings and an overview of the measured and calculated values. The third goal deals with notifying the user about alarms that occur. Here, a Telegram bot was integrated that provides all user information and interactions in a group channel. The bot can inform the users about the current status, as well as about occurring alarms, in addition, simple user interaction with the bot is possible to set the alarms on or off. The integration with the Telegram bot requires an existing bot and a Telegram channel.

Do people learn about the political world through online media? We address this question by developing different exogenous measures of media exposure, drawing on three months of web-tracking data from five democracies. Our analysis distinguishes between visits to general news domains and visits to politically or content-specific articles, identified using machine learning techniques. We evaluate these measures through multiple approaches, including their ability to significantly predict political knowledge. To deepen our understanding, we analyze knowledge gains during a major, unexpected news event—the 2022 Russian invasion of Ukraine—using observed media exposure measures varying in granularity. Our findings underscore the importance of granularity: visits and time spent on Ukraine-related articles emerge as the only significant predictor of surveillance knowledge, while broader measures, such as domain-level visits, show no significant impact when controlling for self-reported exposure and other key predictors. We conclude by discussing the substantive and methodological implications of these results.

Before The Event (BTE) Insurance Market Outlook

The global market size for Before The Event (BTE) Insurance was valued at approximately USD 3.8 billion in 2023 and is projected to reach around USD 6.9 billion by 2032, growing at a CAGR of 6.7% during the forecast period. The growth of this market is significantly driven by an increasing awareness of risk management and the rising number of events being organized worldwide. As businesses and individuals seek to mitigate potential financial losses due to unforeseen circumstances, the demand for BTE insurance is experiencing robust growth.

One of the primary growth factors for the BTE Insurance market is the escalating threat of event cancellations and liabilities. Factors such as unpredictable weather conditions, political unrest, and health emergencies like pandemics have heightened the need for comprehensive insurance coverage to protect against financial losses. Event organizers and businesses are increasingly recognizing the importance of being prepared for such eventualities, which is driving the demand for various forms of BTE insurance such as event cancellation insurance and liability insurance.

Moreover, the proliferation of corporate events, personal celebrations, sports events, and entertainment shows has also fueled the market. Companies are now more than ever investing in large-scale events for marketing and networking purposes, while individuals are spending significantly on weddings, concerts, and other personal events. The financial stakes involved in these events are high, and BTE insurance offers a safety net that ensures peace of mind for organizers and participants alike. This has contributed to the market's robust expansion.

Technological advancements and the rise of online platforms have added another dimension to the market's growth. Digitalization has made it easier for consumers to access insurance products and compare various plans, thereby enhancing market penetration. Online platforms and digital brokers have democratized the access to BTE insurance, making it more convenient for both individuals and businesses to purchase policies tailored to their specific needs. The ease of doing business online is a significant factor driving market growth.

From a regional perspective, North America and Europe hold the largest market shares due to the high frequency of large-scale events and extensive awareness regarding the benefits of BTE insurance. However, the market in regions like Asia Pacific and Latin America is also witnessing rapid growth, driven by economic development and increasing disposable incomes. As these regions continue to host more international events, the demand for BTE insurance is expected to rise accordingly.

Coverage Type Analysis

The BTE Insurance market can be segmented by coverage type into Legal Expense Insurance, Event Cancellation Insurance, Liability Insurance, and Others. Each of these coverage types serves a specific purpose and addresses different aspects of risk management, contributing to the overall robustness of the market.

Legal Expense Insurance is gaining prominence as legal disputes and litigation become more common in today's complex business environment. This insurance type covers the legal costs associated with various types of disputes, providing financial support and peace of mind to policyholders. Businesses and event organizers are increasingly opting for this coverage to protect against the high costs of legal proceedings, which can be financially draining.

Event Cancellation Insurance is perhaps the most sought-after coverage type, especially in light of recent global events such as the COVID-19 pandemic. This insurance covers financial losses resulting from the cancellation or postponement of events due to unforeseen circumstances such as natural disasters, health emergencies, or even terrorism. As the unpredictability of such events increases, so does the demand for this type of insurance.

Liability Insurance is another critical coverage type, providing protection against claims arising from injuries or damages that occur during an event. This type of insurance is essential for event organizers to mitigate the risks associated with large gatherings. With the rise in the number of public events and increasing awareness of potential liabilities, the market for Liability Insurance is expected to grow significantly.

The "Others" category includes various niche insurance products tailored to specific ne

Respondents (%) from each population believing that the individual would have noticed the unexpected event (providing a “yes” response).

This package contains the data, programs, and instructions to replicate manuscript "Revising Beliefs in Light of Unforeseen Events" by Christoph K. Becker, Tigran Melkonyan, Eugenio Proto, Andis Sofianos and Stefan T. Trautmann forthcoming at JEEA.

Accuracy measures of the models based on a split in training set (January 2015 to February 2019) and test sets (March 2019 to December 2019) for the Spanish data.

Traffic Events
This dataset falls under the category Individual Transport Other.
It contains the following data: Data set referring to a traffic accident, traffic accident, road accident or automobile accident is an unforeseen event unrelated to the human factor that alters the normal or planned course of travel on the roads.
This dataset was scouted on 2022-09-30 as part of a data sourcing project conducted by TUMI. License information might be outdated: Check original source for current licensing. The data can be accessed using the following URL / API Endpoint: https://datos.pueblacapital.gob.mx/sites/default/files/Hechos%20de%20Transito%20-%20Julio%202022.csv