Jurnal Online STTKD (Sekolah Tinggi Teknologi Kedirgantaraan)
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Not Such Fast Friends? The Effect of Intimate Conversation on Social Connection in Text-Based Getting Acquainted Interactions
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Forensic Mental Health Expert Bias
No full textThis project will answer questions about experts’ susceptibility to bias. We focus on experts in the legal system (forensic mental health experts) and investigate their vulnerabilities to several biases. We anticipate experts will be highly susceptible to the “bias blind spot”— in fact, we expect experts to exhibit overconfidece in their objectivity. We will test these hypotheses through an experiment designed to measure experts’ actual susceptibility to various biases and their awareness of those susceptibilities
Unconscious emotional conflict in major depressive disorder: A simultaneous EEG-fMRI study
No full textAccording to the cognitive model of depression, biased acquisition and evaluation of emotional infor-mation are the key elements for developing and maintaining depression (Beck, 1987). Maladaptive functions in depression are primarily explained by two mechanisms; i) hyperactive responses to nega-tive information initiate an emotional processing bias, even when the negative information has been unconsciously perceived, and ii) attenuated cognitive control impairs evaluation of the biased infor-mation (for an overview, see Disner et al., 2011). The present project aims to construct an empirical neural model that provides separate mechanisms in clinical depression by which i) emotion processing is biased at an unconscious level and ii) the resulting effects of unconscious processing are controlled on a conscious level.-masked emotional conflict task to a large sample of participants. A multimodal neuroimaging technique with EEG and fMRI is applied.
Licence: CC-By Attribution 4.0 Internationa
Repeated Exposure and Protest Outcomes: How Fridays for Future Protests Influenced Voters
No full textDo climate protests influence elections? How does repeated exposure influence protest outcomes? In this paper, I build on social-psychological work to argue that a key characteristic of effective protests is their ability to repeatedly expose voters to their message. I test this argument by studying the effect of Fridays for Future (FFF) protests on voting for Green Parties. Using a novel dataset of FFF protests and a difference-in-differences design, I find that exposure to climate protests increases the vote share of the German Greens, and that repeated exposure to protests increases this effect. Additional analyses suggest that this increase is driven by higher voter turnout and shifts in climate attitudes, but not by changes in the issue salience of climate change. These patterns are replicated in six other European democracies. These findings are important to understand when protests influence behaviour, and the political consequences of climate protests
g-distance: On the comparison of model and human heterogeneity
No full textModels are often evaluated when their behavior is at its closest to a single, sometimes averaged, set of empirical results, but this evaluation neglects the fact that both model and human behavior can be heterogeneous. Here, we develop a measure, g-distance, which considers model adequacy as the extent to which models exhibit a similar range of behaviors to the humans they model. We define g as the combination of two easilyinterpretable dimensions of model adequacy: accommodation and excess flexibility. We apply this measure to five models of an irrational learning effect, the inverse baserate effect (IBRE). g-distance identifies two models, a neural network with rapid attentional shifts (NNRAS) and a dissimilarity-similarity generalized context model (DGCM18), that outperform the previously most supported model (EXIT). We show that this conclusion holds for a wide range of beliefs about the relative importance of excess flexibility and accommodation. We further show that a pre-existing metric, the Bayesian Information Criterion (BIC), misidentifies a known-poor model of the IBRE as the most adequate model. Along the way, we discover that some of the models accommodate human behavior in ways that seem unintuitive from an informal understanding of their operation, thus underlining the importance of formal expression of theories. We discuss the implications of our findings for model evaluation generally, and for models of the inverse base-rate effect in particular, and end by suggesting future avenues of research in computational modeling
De-identification when making datasets FAIR: Two worked examples from the behavioral and social sciences
No full textIn recent years, the advancement of open science has led to data sharing becoming more common practice. Data availability has clear merits for science as it opens up possibilities for re-use of datasets by others, leading to less redundancy, more efficiency, and more transparency. The ideal is for scientific data to be as open as possible and FAIR: Findable, Accessible, Interoperable, and Reusable. Parallel to this development, recent times have seen more stringent guidelines with respect to data privacy, culminating in the General Data Protection Regulation law, or GDPR. Navigating the balance between protecting participants’ privacy and making one's dataset as open as possible can be challenging for researchers. In this paper, we provide two worked examples with real datasets from the behavioral and social sciences on how to be as open as possible and as closed as necessary, with the goal of maximally facilitating science while minimizing the risk of participant identification