“…As scoring evidence could be subjective, we conducted an inter‐rater reliability test (Box 2) to assess the consistency with which different individuals scored the different aspects of the weight and strength of support of a range of pieces of evidence for different assumptions (rating using numerical scores from 0 to 3 based on the Table 1 categories). We found mostly “strong,” or at least “satisfactory,” agreement between individuals in how they applied this scoring system (Finn, 1970; Gamer et al, 2012). As will be discussed later, it is important that the composition of the decision‐making body or group assessing the evidence is as diverse and inclusive as possible, with a range of expertise and experience so that the collation and assessment of evidence (and ultimately decision‐making; Hemming, Burgman, et al, 2018; Hemming, Walshe, et al, 2018) is high quality and not systematically biased against any particular source of evidence.…”
Section: A Process To Assess Assumptions Using Evidencementioning
Meeting the urgent need to protect and restore ecosystems requires effective decision‐making through wisely considering a range of evidence. However, weighing and assessing evidence to make complex decisions is challenging, particularly when evidence is of diverse types, subjects, and sources, and varies greatly in its quality and relevance. To tackle these challenges, we present the Balance Evidence Assessment Method (BEAM), an intuitive way to weigh and assess the evidence relating to the core assumptions underpinning the planning and implementation of conservation projects, strategies, and actions. Our method directly tackles the question of how to bring together diverse evidence whilst assessing its relevance, reliability, and strength of support for a given assumption, which can be mapped, for example to a Theory of Change. We consider how simple principles and safeguards in applying this method could help to respectfully, and equitably, include more local forms of knowledge when assessing assumptions, such as by ensuring diverse groups of individuals contribute and assess evidence. The method can be flexibly applied within existing decision‐making tools, platforms, and frameworks whenever assumptions (i.e., claims and hypotheses) are made. This method could greatly facilitate and improve the weighing of diverse evidence to make decisions in a range of situations, from local projects to global policy platforms.
“…As scoring evidence could be subjective, we conducted an inter‐rater reliability test (Box 2) to assess the consistency with which different individuals scored the different aspects of the weight and strength of support of a range of pieces of evidence for different assumptions (rating using numerical scores from 0 to 3 based on the Table 1 categories). We found mostly “strong,” or at least “satisfactory,” agreement between individuals in how they applied this scoring system (Finn, 1970; Gamer et al, 2012). As will be discussed later, it is important that the composition of the decision‐making body or group assessing the evidence is as diverse and inclusive as possible, with a range of expertise and experience so that the collation and assessment of evidence (and ultimately decision‐making; Hemming, Burgman, et al, 2018; Hemming, Walshe, et al, 2018) is high quality and not systematically biased against any particular source of evidence.…”
Section: A Process To Assess Assumptions Using Evidencementioning
Meeting the urgent need to protect and restore ecosystems requires effective decision‐making through wisely considering a range of evidence. However, weighing and assessing evidence to make complex decisions is challenging, particularly when evidence is of diverse types, subjects, and sources, and varies greatly in its quality and relevance. To tackle these challenges, we present the Balance Evidence Assessment Method (BEAM), an intuitive way to weigh and assess the evidence relating to the core assumptions underpinning the planning and implementation of conservation projects, strategies, and actions. Our method directly tackles the question of how to bring together diverse evidence whilst assessing its relevance, reliability, and strength of support for a given assumption, which can be mapped, for example to a Theory of Change. We consider how simple principles and safeguards in applying this method could help to respectfully, and equitably, include more local forms of knowledge when assessing assumptions, such as by ensuring diverse groups of individuals contribute and assess evidence. The method can be flexibly applied within existing decision‐making tools, platforms, and frameworks whenever assumptions (i.e., claims and hypotheses) are made. This method could greatly facilitate and improve the weighing of diverse evidence to make decisions in a range of situations, from local projects to global policy platforms.
“…The assessment data was collected separately for the adults' and high school students' speech samples, and the assessment processes are described in detail in [6] and [17]. In these studies, the inter-rater reliability was tested with intraclass correlation coefficient (ICC) using the irr package in R [22]. The average type ICC was selected as reliability measure, since it takes into account the scope of disagreement by comparing individual ratings of a sample to the mean rating of the sample.…”
Section: Speech Data and Human Assessmentsmentioning
Fluency is a commonly used descriptor of second language (L2) speaking skills. Unplanned and too frequent pauses, hesitations, and repetitions disrupt the flow of speech and can cause temporal irregularities at all levels of speech hierarchy, from syllable rate to phrasing. However, most studies that attempt to quantify fluency disregard pause locations. The current study investigates, whether and which pause locations affect the perceived fluency and proficiency in L2 Finnish.Several pause parameters were computed from spontaneous L2 Finnish speech samples. Pause locations were investigated with regards to clauses and phrases as well as incomplete words. The effect of pause locations to human assessments of fluency and proficiency was investigated using linear regression models.The results suggest that silent and filled pauses within phrases and pauses after incomplete words significantly reduce the fluency of L2 Finnish speech, whereas pauses within clauses may even have a positive effect on fluency and proficiency. The results support the role of phrases over clauses as bases for prosodic grouping in spontaneous Finnish, but further research is needed with native speakers of Finnish. Furthermore, the results encourage to investigate the role of pause location parameters in comprehensive models for L2 speech fluency.
“…In an initial version, the AIS Class A station available on the ship can be used. In order to increase the availability and reliability of data and communications received, it will be necessary to analyse and evaluate the inclusion of redundant equipment in the system (Gamer et al, 2014).…”
Maritime accident statistics reveal that ship collisions are among the most frequent and severe accidents. The same statistics indicate that most of them are caused by human error, mainly due to breaches of the International Regulations for Preventing Collisions at Sea (COLREGs) and to the lack of communication between ships. There are also special situations where there is some ambiguity in the application of the COLREGs. In such occasions, and if there is no communication between the ships involved, compliance with the Rules may still end up in a collision. This article brings a new approach to Collision Avoidance Systems (CAS) and presents the earliest stages in the development of safety functions for the reduction of ship-to-ship collision risk on the high seas. These functions will help the concerned ships achieve coordinated compliance with the COLREGs. Functional safety standards are applied and, in their implementation, real, accessible electronic programmable systems (hardware and software) will be used.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.