Pseudocontingencies – rule based and associative

The present work puts forward a rule-based model for judging the direction of a contingency. A set of “alignment rules” (ARs) is defined, all of which bind frequent observations to frequent observations and infrequent observations to infrequent observations. These rules qualify as possible mechanisms behind pseudocontingencies (PCs, Fiedler, Freytag, & Meiser, 2009). Six experiments, involving social and non-social stimuli, are presented that pit the predictions of the rule-based PCs against associative models for contingency judgments (Van Rooy, Van Overwalle, Vanhoomissen, Labiouse, & French, 2003). Results consistently show that participants associate predictors with criteria that are non-contingent but jointly frequent and rare. Crucially, these illusory contingency judgments are shown to persist (a) in attitude ratings after extended observational learning and (b) at asymptote in operant learning. In sum, the results are evidence for the impact of rule-based PCs under conditions that call for associative learning. In a next step, rational arguments (Anderson, 1990) are used to set the AR apart from other rule-based models with similar empirical predictions. Results of two simulations reveal that the AR performs remarkably well under real-life constraints. Under clearly definable conditions, like strongly skewed base rates and small observational samples, the AR performs even better than other models, like ΔP (Allan, 1993) or the Sum-of-Diagonals (SoD, Inhelder & Piaget, 1958). Finally, the AR is claimed to be a natural by-product of the learning history with strong contingencies. Suggestive evidence from a simulation is provided that shows an increased likelihood of jointly skewed base rates, the precondition for ARs, in the presence of strong contingencies. Thus, ARs might develop from a confusion of the learned above chance probability p ( joint-skew | strong-contingency ) with an above chance probability p ( strong-contingency | joint –skew ) that justifies an AR inference. Possible future research on how joint observations and base-rates interact to influence contingency judgments is outlined

Base-rate neglect based on base-rates in experience-based contingency learning

Predicting criterion events based on probabilistic predictor events, humans often lend excessive weight to predictor event information and insufficient weight to criterion event base-rates. Using the matching-to-sample paradigm established in studies on experience-based contingency learning in animals, Goodie and Fantino (1996) showed that human judges exhibit base-rate neglect when sample cues are associated with response options through similarity relations. In conceptual replications of these studies, we demonstrated similar effects when sample cues resemble the response options in terms of base-rates skewed in the same direction rather than physical similarity. In line with the pseudocontingency illusion (Fiedler & Freytag, 2004), predictions were biased toward the more (less) frequently rewarded response option following the more (less) frequently presented sample cue. Thus, what is a demonstration of base-rate neglect from one perspective turns out to reflect the judges' sensitivity to the alignment of skewed base-rate distributions.

Base-rate neglect based on base-rates in experience-based contingency learning

Predicting criterion events based on probabilistic predictor events, humans often lend excessive weight to predictor event information and insufficient weight to criterion event base-rates. Using the matching-to-sample paradigm established in studies on experience-based contingency learning in animals, Goodie and Fantino (1996) showed that human judges exhibit base-rate neglect when sample cues are associated with response options through similarity relations. In conceptual replications of these studies, we demonstrated similar effects when sample cues resemble the response options in terms of base-rates skewed in the same direction rather than physical similarity. In line with the pseudocontingency illusion (Fiedler & Freytag, 2004), predictions were biased toward the more (less) frequently rewarded response option following the more (less) frequently presented sample cue. Thus, what is a demonstration of base-rate neglect from one perspective turns out to reflect the judges' sensitivity to the alignment of skewed base-rate distributions

Pseudocontingencies in stereotype formation : extending illusory correlations

Under the notion of illusory correlations, simple learning paradigms (e.g. Hamilton & Gifford, 1976) have been used to study the formation of stereotypes that discriminate between majorities and minorities. In the present paper, limitations of this approach in terms of theoretical explanations and empirical evidence are addressed. Theoretically, we propose pseudocontingencies (PCs, Fiedler, Freytag & Meiser, 2008) as a more robust mechanism behind illusory correlations. In contrast to previous explanations, PCs can explain illusory correlations when groups are never paired with valence. Empirically, we replicate earlier findings, i.e. that the more frequently observed group, the majority, is evaluated more in line with the more frequently observed valence. Crucially, we extend the empirical evidence in that illusory correlations prove robust over a very large number of observations (320) and under increasingly interactive task conditions, involving predictions of valence (Experiment 2) and reinforcement-learning conditions (Experiment 3). The latter provided evidence for illusory correlations on a new measure, participants’ predictions. These predictions reflect the expectations about the valence associated with majority and minority and might well affect real life behavior. The discussion focuses on possible reasons for why PCs are used in stereotypic judgments

The reproduction of base-rates promotes pseudocontingencies

Fiedler and Freytag (2004) proposed an alternative pathway to contingency assessment in terms of pseudocontingencies (PCs). PCs reflect the utilization of base-rate information in the formation of contingency judgments. Here, we introduce an instantiation of the phenomenon based on the mere reproduction of the base rates. Using a relationship-counseling scenario, participants in two experiments produced positive correlations on both indirect and direct measures of the contingency between partners’ responses to the subscales of a relationship inventory, although the objective contingency within each subscale had been negative in an initial learning phase. The magnitude of these effects was predicted accurately by computer simulations reproducing the base rate of ‘yes’ responses for each partner and domain. The findings are discussed within the PC framework

Impact of incentives for greener battery electric vehicle charging - A field experiment

Battery electric vehicles generate a significant share of their greenhouse gas emissions during production and later, when in use, through the energy used for charging. A shift in charging behavior could substantially reduce emissions if aligned with the fluctuating availability of renewable energy. Financial incentives and environmental appeals have been discussed as potential means to achieve this. We report evidence from a randomized controlled trial in which cost-free and “green” charging was advertised via email notifications to customers of a charging service provider. Emails invited to charge during midday hours (11:00 to 15:00) of days with high predicted shares of renewable energy. Results show a significant increase in the number of charging processes in the critical time, and in the amount of energy charged (kWh), despite only marginal monetary savings of 5€ on average. A further increase in kWh charged was observed on weekends. Under the assumption that these charging processes replaced regular overnight charging at home, this represents reduction in CO2 emissions of over 50%

MUSCULOSKELETAL SQUAT SIMULATION EVALUATION BY MEANS OF AN INSTRUMENTED TOTAL KNEE ARTHROPLASTY

Knowledge of internal loading conditions based on validated musculoskeletal (MS) simulations can allow improved training and rehabilitation design and monitoring. The aim of this study was to evaluate the ability of individualised reference MS models, based on comprehensive motion analysis, to determine knee joint contact forces (JCFs), as measured in 6 subjects with instrumented total knee arthroplasties (TKA) during squat exercises. Maximum simulated JCFs reached approximately 100% higher than the in vivo measured values at high joint flexion angles; however, at knee flexion angles of below -l0 degree, the models underestimated the real forces by up to 50%. Improvements of reference MS models, even if they are individualised, are clearly required, especially at joint angles -50 degree