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Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology
Get PDFAlthough variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future
Paradoxes and trade-offs in the front-end process of large public projects
Get PDFThe aim of this conceptual paper is to contribute to a better understanding of the front-end phase of large public projects, which is complex and non-linear. The point of departure relates to a number of paradoxes found along the way of the front-end. A processual approach is taken to follow the front-end over time. Considering a number of example vignettes, four paradoxes and subsequent trade-offs are discussed which affect the strategic decisions that need to be made. These are found to fit largely within four generic sub-processes identified in the front-end. Inspired from the paradox theory, we conceptualise paradoxes and trade-offs under the dynamic equilibrium model adapted for temporary organising such as large public projects. Main aim of this paper is to consider how decision-making can be improved, and managerial strategies developed that permit the acceptance of paradoxes and their resolution in a virtuous cycle leading to long term success
Play and Sustainability
No full textThis chapter discusses the concept of sustainability as a lens to understand how the world of play enables adults to engage and learn about sustainability with and for young children in environments that enable. Scollan and Farini introduce environments that enable as rights-based spaces where children and adults intuitively move between learning and teaching through immersion into play and meaningful dialogue (Scollan and Farini, 2021; Farini and Scollan, 2023). Early Childhood is a critical period for developing positive relationships with nature and a deep empathetical connection with our planet. The fundamental values underpinning positive relationships with nature are encompassed in the 3 Pillars of Sustainability; socio-cultural justice, environmental empathy of people and places, and, economical awareness. Boyd’s (2025) Pillars of Sustainability and the UNESCO (2015) Sustainable Development Goals (SDG) below can help us make the connection between play and sustainability in everyday practice
The impacts of human-made structures on larval connectivity in the northern North Sea
Get PDFNorth Sea human-made, offshore structures (e.g. oil/gas platforms, offshore wind farms) provide a hard substrate habitat for benthic marine species which can spread between sites during their larval stage. Here, we aim to address how the installation of additional human-made structures, like new wind farms, or decommissioning of existing ones, like oil and gas platforms at the end of service, contribute to changes in larval connectivity. We use particle tracking model simulations to assess the ecological connectivity of benthic species in the northern North Sea during two contrasting years to highlight seasonal to annual variability. The methodology of releasing an extensive set of particles over a wide area produces our Retrospective Particle Tracks dataset. The sets of simulations can be interrogated to understand if additional human-made structures placed in any locations in the northern North Sea could potentially affect the ecological connectivity. Network metrics were used to identify connectivity between sites. Clustering of existing structures identifies a region that acts as an interchange between other structures which may otherwise only be connected during intermittent periods. The addition of new human-made structures located in areas with stronger residual current flow would enhance the connectivity
Credibility and influence in health messaging: examining medical professionals' role on X in promoting N95 respirators during COVID-19
No full textThis study explores the role of health influencers on X (formerly Twitter) in promoting N95 respirators, with a focus on the accuracy and completeness of the information shared. It evaluates the impact of X influencers on public perception and policy regarding N95 masks. Using a tripartite model integrating eWOM, health messaging, and opinion leadership, the research analyzed 251,740 tweets through social network analysis (SNA) and content analysis. A systematic random sample of 21,436 tweets reveals that influencers with +100k followers and verified accounts achieved higher engagement. While health influencers played a significant role in shaping public understanding, gaps in detailed guidance highlight the need for actionable and precise messaging. Positioned at the intersection of public policy and marketing, our study emphasizes influencer collaboration and standardized communication strategies to improve health information dissemination on digital media
An independent view: rebuilding trust and confidence in policing within minority communities
No full textOpening paragraph:To understand the current situation between minority communities and policing in the UK, we must first examine the historical context. In the UK, the legacy of colonialism and the over-policing of Black and Asian communities during the 20th century have left lasting scars. These historical injustices have created a legacy of mistrust. For many minority communities, the police are not seen as protectors but as oppressors. This perception is reinforced by contemporary issues such as racial profiling, disproportionate use of force, and the overrepresentation of minorities in the criminal justice system. One key example is stop and search statistics. In 2022 -23, the rate for stop and search was 4.1 times higher for people identifying as Black or Black British compared to those from a white ethnic group (Figure 1). Those who were stop and searched often considered it a negative and traumatic experience. Until these historical and systemic issues are acknowledged and addressed, rebuilding trust will remain an elusive goal
Enhancing Cybersecurity in Internet of Vehicles: A Machine Learning Approach with Explainable AI for Real-Time Threat Detection
Get PDFThe proliferation of IoV technologies has revolutionized the use of transport systems to a great level of improvement in safety and efficiency, and convenience to users. On the other hand, increased connectivity has also brought new vulnerabilities, making IoV networks susceptible to a wide range of cyber-attacks. The contribution of this paper is the in-depth study of the development and evaluation of advanced machine learning (ML) models that detect and classify network anomalies in IoV ecosystems. Several classification models have been studied in our research to achieve high accuracy for discriminating between benign and malicious traffic. This work further harnesses Explainable AI (XAI) methodolo-gies through the LIME framework for enhanced interpretability of models' decision-making processes. Experimental results strongly advocate the strength of Random Forest and XGBoost, proving to be better on the binary and multi-class classification tasks, respectively. Due to resilience, preciseness, and scalability these models are a practical choice in real-world IoV security frameworks. Ex-plainability integrated not only strengthens model reliability but also closes the gap between performance and interoperability in vehicular networks. CCS CONCEPTS • Computing methodologies → Supervised learning by classification
A review of the Boat Bug Enoplops scapha: a nationally scarce coreid with an outlying North Yorkshire population
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Scour mitigation measures around offshore wind structures using experimental models.
Get PDFMotivated by the expansion of the offshore wind industry, research on scour around subsurface structures has gained momentum in recent years. This study focuses on flow-altering scour mitigation methods which would be suitable for use within the offshore environment. This research project incorporates the design and execution of a numerical study alongside extensive experimental investigations. These investigations aim to explore scour processes and identify effective mitigation strategies for offshore structures.Following a comprehensive review of existing scour mitigation methods, the research focused on exploring alternatives to traditional rock armour, this objective guided the formulation of research aims for this thesis. The study incorporated a fundamental understanding of scour processes, specifically the effect of structure-induced flow patterns on the downflow, horseshoe vortex, and lee-wake vortices. Numerous alternative mitigation methods were evaluated in a controlled experimental model to assess their effectiveness in mitigating scour. These methods included collars of varying diameters positioned at different elevations relative to the bed, collars incorporating textured vegetation, rock bags, and textured piles. A novel data collection technique utilising an acoustically transparent Mylar Film was implemented to facilitate continual monitoring of bed changes beneath the collars. The experimental investigations were conducted in a laboratory setting under various flow regimes, including unidirectional clear water and live bed flows, as well as additional tests simulating bi-directional currents.This research yielded a multitude of original results and established a novel data collection method using Mylar Film for continuous under-collar monitoring. The findings presented in this thesis demonstrate that the use of collars at optimal heights and diameters with and without added texture offers viable alternatives to traditional rock armour for scour mitigation. This work will contribute to the advancement of scour mitigation methods and experimental model investigations
THE BRAIN, A PREDICTIVE MACHINE?: Cortical oscillations of anticipating and observing actions in ASD and typically developing people.
Get PDFA fundamental human capacity is to construct predictive representations of upcoming events (the brain as a predictive machine). This is of special relevance within the social world, where the events that matter most are others’ actions, and whose accurate prediction/anticipation critically affects social success. The study of action prediction in social contexts is therefore a relevant issue in the Cognitive Neurosciences and Psychology, although it is a thoroughly complex and challenging task. A promising framework to study action prediction is the Mirror Neuron System (MNS), located in the sensorimotor cortex, which becomes active during both the execution and observation of actions. There has been a lot of speculation about the functional significance of the MNS. One interpretation, which will be pursued in the current studies, is that it is involved in the automatic understanding of others’ actions, i.e. an ‘experiential’ understanding ‘from within’. Traditionally, the MNS has been thought to respond only reactively, not predictively, when observing actions. However, recent single-cell studies in monkeys support a predictive role for the MNS. That is, provided contextual cues allow them to predict the upcoming action. There is some intriguing evidence for an action anticipation impairment in autism spectrum disorder (ASD). Studies with ASD children suggested that, crucially, the chaining of the subsequent acts that together make up an action, is impaired. This motor chaining is crucial because it allows one to ‘take a peek into the future’ when the chain automatically unfolds like a row of falling dominoes. However, testing of adults with ASD has shown inconclusive results concerning their capability to predict actions, possibly reflecting their use of compensatory mechanisms. Aswell, the differences between different experiment conditions (age of the participants, type of stimuli, ecological validity, differences within the spectrum of autism) have made it difficult to compare results of mirror neuron functions in ASD people.In this research we aimed to test the contentious idea that the ability to predict/anticipate other’s (upcoming) actions is underpinned by the concerted activation of ‘action-chains’ in the Mirror Neuron System, which has been suggested by some researchers to be impaired in ASD. To this aim, we collected the EEG data of adult participants with autism and of those high on autism traits, and neurotypical controls, while they observed sequences of actions between two interacting agents (either biological agents or non-biological agents). Each trial started with the still hands of the two agents depicted facing each other. The sequence of events included in some cases a predicting cue announcing that the first agent was going to perform an action (giving a card to the second agent) and the second agent was going to respond to that action (picking up the card that was given), or a unpredictable cue with no information on the incoming events (either first agent giving a card or not giving a card, second agent picking up the card or not picking up the card in case it was given to them). In parallel, there were non-biological stimuli, consisting of rectangular shapes (bars) rather than hands, “transferring” an object or not “transferring” it, with the same motion patterns and velocities as in the biological conditions. We measured the modulation of mu rhythms (8-13 Hz) at central, centroparietal and parietal areas, as a signature of MNS activity. Crucially, mu suppression was recorded not only during the performance of biological and non-biological motions, but also during the period preceding the motion, after the prediction cue was shown. Additionally, we measured the activity of occipital alpha in the occipital electrodes to compare such alpha band activity with mu rhythm in sensorimotor area. We found that both experimental participants (those with autism/high autistic traits) and control participants (neurotypical) showed mu suppression during the time windows when an action was performed (either the action of the first or of the second agent for both biological and non-biological stimuli) without differences. We also found that prediction has a marginal effect in the first anticipation phase (either biological or non-biological) or no effect in mu oscillations during the second anticipation of an action. Moreover, differences between predictable and unpredictable conditions or between action and no action conditions were found only in typically developed participants. High autistic participants (experimental group) did not show differences between predictable and unpredictable contexts, with even greater mu desynchronization in some unpredictable conditions. The same pattern was found in the difference between action and no action contexts: high autistic trait groups did not show such difference, sometimes desynchronizing mu band even more in the prediction of no action conditions in the mu band.This research hopes to establish how MNS interacts to produce a mechanism enabling action prediction/anticipation, which challenges the current MNM interpretation. It would help to understand joint actions and automatic action understanding, which form the bedrock of social interaction and education. Gaining an understanding of the characteristics of ASD/autistic traits is essential in comprehending how individuals on the spectrum read, process, and interpret social cues, particularly in relation to anticipating future events