This study replicated an earlier study that explored the beliefs of a sample of K-8 pre-service teachers (PSTs). Results of this study position PSTs' beliefs along a traditional-reform continuum. The positioning from the current study is compared to that of the former study, to determine the level of progress made toward the National Council of Teachers of Mathematics' commitment to high-quality instruction. To position beliefs, PSTs completed a Likert survey, including open-ended questions, three times throughout their teacher preparation program (TPP): before taking any of their mathematics education courses, after taking both required mathematics education courses, and after student teaching. On the last survey iteration, PSTs completed additional Likert items and open-ended questions regarding their teaching practices. Analysis centered on the relationship between each iteration of the new survey, comparisons to results from the initial study, and the alignment between beliefs and teaching practices. Overarching results convey that even with the passage of eleven years, the positioning of beliefs and teaching practices remained relatively static. Beliefs related to the power of student ideas, mathematical processes, productive disposition, and productive struggle were categorized as being reform oriented. The perception that mathematics is mostly computation and that the expository teaching is the most effective way to teach mathematics were categorized as being strongly traditional. Beliefs that were categorized more centrally related to collaboration and the emphasis on answers. Suggestions are provided for teacher educators to continue their work toward reforming beliefs about mathematics and how to teach mathematics.
Philosophers have long speculated that individual differences in temperament influence philosophical thinking, yet empirical research has rarely explored the role of neurodivergent traits in this domain. In this large online study (N = 1,254), we investigated whether participants with training in philosophy differ from the general population when it comes to six psychological traits - autism, ADHD, aphantasia, anendophasia, anauralia, and representational manipulation - and also whether these traits correlate with responses to two widely studied philosophical thought experiments: the "trolley problem" and the "rollback deterministic universe." Compared to the general population, participants with training in philosophy had higher scores on measures of ADHD, internal verbalization, and representational manipulation, but lower scores on measures of visual imagery. These cognitive traits were also correlated with participants' moral and metaphysical judgments (independent of their level of philosophical training) - e.g. participants who scored higher in visualization were less likely to judge that hitting the switch in the trolley problem is permissible but not obligatory, and also less likely to attribute free will and moral responsibility to agents in the rollback universe. Finally, we employed machine learning to develop predictive models that classify a randomly selected participant as either a philosopher or a non-philosopher. Models trained solely on responses to measures for neurodivergent traits achieved better performance than models trained solely on responses to philosophical thought experiments. This suggests that stable, trait-level neurodivergent characteristics may be more diagnostic of philosophical interest, aptitude, or training than judgments philosophers make on domain-relevant problems.
PurposeThis study investigates how project-level textual and contextual characteristics influence the number of bids received in online labor markets (OLMs). Specifically, it examines whether features such as readability, length, sentiment, technical specificity, budget and contract type serve as signals that affect freelancer engagement.Design/methodology/approachUsing a dataset of over 47,000 project listings, the study employs natural language processing (NLP) and machine learning techniques to extract structured variables from unstructured project descriptions. Multinomial logistic regression and ordinary least squares (OLS) models are used to evaluate the impact of these features on bid volume. Interaction effects between readability and sentiment, and between length and budget, are also examined.FindingsThe results show that more complex (i.e. less readable) and longer project descriptions are associated with higher bid volume. A positive emotional tone significantly increases freelancer engagement, and fixed-price contracts are more likely to attract bids than hourly ones. Technical specificity, while generally reducing the number of bids, may help filter for more qualified freelancers. Interaction effects indicate that the positive impact of sentiment is amplified when descriptions are easier to read, and that longer descriptions are more effective when the budget is larger.Originality/valueThis research contributes to the literature by introducing machine-learned textual features as behavioral signals in OLMs and highlighting the interplay between content quality and structural attributes. It offers practical guidance for clients and platforms seeking to improve project engagement and market efficiency.
Context. Orbiting matter misaligned with a spinning black hole undergoes Lense-Thirring precession due to the frame-dragging effect. This phenomenon is particularly relevant for type-C QPOs observed in the hard states of low-mass X-ray binaries. However, the accretion flow in these hard states is complex, consisting of a geometrically thick, hot corona surrounded by a geometrically thin, cold disk. Recent simulations demonstrate that, in such a truncated disk scenario, the precession of the inner, hot corona slows due to its interaction with the outer, cold disk. Aims. This paper aims to provide an analytical description of the precession of an inner (hot) torus in the presence of accretion torques exerted by the outer (cold) disk. Methods. Using the angular momentum conservation equation, we investigated the evolution of the torus angular momentum vector for various models of accretion torque. Results. We find that, in general, an accretion torque tilts the axis of precession away from the black hole spin axis. In all models, if the accretion torque is sufficiently strong, it can halt the precession; any perturbation from this stalled state causes the torus to precess around an axis that is misaligned with the black hole spin axis. Conclusions. The accretion torque exerted by the outer thin disk can cause precession around an axis that is neither aligned with the black hole spin axis nor perpendicular to the plane of the disk. This finding may have significant observational implications, as the jet direction, if aligned with the angular momentum axis of the torus, may no longer reliably indicate the black hole spin axis or the orientation of the outer accretion disk.
Extreme heat events are becoming a growing concern for urban residents, with increased frequency and intensity. Understanding urban heat dynamics and thermal exposure is critical for identifying and mitigating heat hazards. Most studies of urban heat dynamics use satellite-derived or weather station data that are limited in temporal and spatial resolutions. Improving urban sustainability requires new ways to capture hyperlocal ambient air temperature (AAT) information within complex, built environments. Drive-by-sensing offers great potential in capturing the spatiotemporal dynamics of urban heat. Our paper demonstrates the broader application of temporally dense hyperlocal AAT data obtained using a novel drive-by-sensing framework. Using 2 million AAT data points collected between May-September 2019, we examine the thermal complexities of a mid-sized city, including the spatio-temporal dynamics of hotspots and areas of extreme heat exposure. This high spatiotemporal dataset reveals differing heat profiles under different weather conditions and at different times of day, with temperature variations of up to 12 degrees C between hot and cold spots. These hotspots move around the city and were not all found near urban cores. This drive-by-sensing approach has the potential to be scaled and used by government entities to make cities more heat resilient and sustainable.
