Assessment of individual competence

Aims: the assessment of individual competence in medical education is about finding a balance between having sufficient resources to make valid and reliable decisions and not using more resources than necessary. Sequential assessment, in which more resources are used for borderline performing candidates than for poorly or clearly satisfactorily performing candidates, can be used to achieve that balance. Although sequential assessment is commonly associated with larger groups of candidates to be assessed, in many practical settings numbers of candidates may be small.Objective: this article presents a single case design with a statistical model for the assessment of individual competence that can be used regardless of the number of candidates.Method: a worked example of a solution that can be used for an individual candidate, using simulated data in the zero-cost Open Source statistical program R version 4.0.5., is provided.Results: the aforementioned solution provides statistics that can be used to make pass/fail decisions at the level of the individual candidate as well as to make decisions regarding the length and timing of an exam (or parts thereof) for the individual candidate.Conclusion: the solution provided can help to reduce resources needed for assessment to a considerable extent while maximizing resources for borderline candidates. This facilitates both decision making and cost reduction in assessment.

High-resolution genetic mapping of the mucosa-associated gut microbiome in hybrid mice provides novel insight on the impact of host genetics

Determining the forces that shape diversity in host-associated bacterial communities is critical to understanding the evolution and maintenance of meta- organisms. To gain novel insight on the genetics of gut microbial traits, we employed a powerful approach using inbred lines derived from the hybrid zone of two incipient house mouse species. We identify a high number of mucosa-associated bacterial taxa with significant heritability estimates, particularly for 16S rRNA transcript-based traits. Interestingly, heritability estimates also positively correlate with cospeciation rate estimates. Association mapping identifies 443 loci influencing 123 taxa, whose narrow genomic intervals enable promising individual candidate genes and pathways to be pinpointed. These results indicate a unique genetic architecture for cospeciating taxa, a clear enrichment for several classes of human disease, and identify important functional categories including innate immunity and G-protein-coupled receptors, whose role in host-microbe interactions diverge as new species form.

Immigrants Serving in Local Government: A Systematic Review and Meta-Analysis of Factors Affecting Candidacy and Election

Descriptive representation, the extent to which politicians reflect the descriptive characteristics (e.g., ethnicity or gender) of their constituents, has been studied at various scales since it was first introduced in Hanna Pitkin's seminal work several decades ago. In recent years, scholars have also begun to investigate immigrant representation in politics, including at the local, state, and national levels of government. This study evaluates the current research on the factors affecting the election of immigrant candidates to municipal government. In addressing the lack of data-driven reviews in this type of research, the paper employs a scoping review methodological framework. Fifty-six distinct factors are identified as important for immigrants’ electoral fortunes. The factors are classified under: Macro-level electoral structures and situational elements, meso-level immigrant group dynamics, and micro-level individual candidate characteristics. The most salient factors are elaborated on, together with a discussion on policy implications and future potential areas of inquiry.

PENCALONAN KEPALA DAERAH PADA PEMILIHAN SERENTAK 2020 DI SULAWESI SELATAN

The concurrent election 2020 in South Sulawesi faced dynamic circumstances as the pairs of candidates must fill the requirements when registering themselves. During the process of regional election, some cases happened in some regions in South Sulawesi. As an example, some candidates in some regions might lose support from the political parties in the middle of the election process as the support from the political party is unstable. On the other hand, special cases happened in two districts (Gowa and Soppeng), where there was only one single candidate for each region. Hence the struggle to get the support of a political party did not occur in both areas. In another region, Selayar, the individual candidate who has already fulfilled the minimum requirement still seeks support from political parties. All candidates tend to register themselves as fast as possible to prevent the failure in registration stage. Another case shows that there was a pair of candidates who failed to be a partner because they were tested positive for narcotics use, while two candidate pairs experienced a delay in registration because they were positive for Covid-19 and the had to wait until they were tested negative for Covid-19 before continuing to the medical check-up stage.

An inexpensive retrospective standard setting method based on item facilities

Background Standard setting is one of the most challenging aspects of assessment in high-stakes healthcare settings. The Angoff methodology is widely used, but poses a number of challenges, including conceptualisation of the just-passing candidate, and the time-cost of implementing the method. Cohen methodologies are inexpensive and rapid but rely on the performance of an individual candidate. A new method of standard setting, based on the entire cohort and every item, would be valuable. Methods We identified Borderline candidates by reviewing their performance across all assessments in an academic year. We plotted the item scores of the Borderline candidates in comparison with Facility for the whole cohort and fitted curves to the resulting distribution. Results It is observed that for any given Item, an equation of the form y ≈ C. eFx where y is the Facility of Borderline candidates on that Item, x is the observed Item Facility of the whole cohort, and C and F are constants, predicts the probable Facility for Borderline candidates over the test, in other words, the cut score for Borderline candidates. We describe ways of estimating C and F in any given circumstance, and suggest typical values arising from this particular study: that C = 12.3 and F = 0.021. Conclusions C and F are relatively stable, and that the equation y = 12.3. e0.021x can rapidly be applied to the item Facility for every item. The average value represents the cut score for the assessment as a whole. This represents a novel retrospective method based on test takers. Compared to the Cohen method which draws on one score and one candidate, this method draws on all items and candidates in a test. We propose that it can be used to standard set a whole test, or a particular item where the predicted Angoff score is very different from the observed Facility.

An Inexpensive Retrospective Standard Setting Method Based on Item Facilities

BackgroundStandard setting is one of the most challenging aspects of assessment in high-stakes healthcare settings. The Angoff methodology is widely used, but poses a number of challenges, including conceptualisation of the just-passing candidate, and the time-cost of implementing the method. Cohen methodologies are inexpensive and rapid but rely on the performance of an individual candidate. A new method of standard setting, based on the entire cohort and every item, would be valuable.MethodsWe identified Borderline candidates by reviewing their performance across all assessments in an academic year. We plotted the item scores of the Borderline candidates in comparison with Facility for the whole cohort and fitted curves to the resulting distribution.ResultsIt is observed that for any given Item, an equation of the form y ≈ C.eFxwhere y is the Facility of Borderline candidates on that Item, x is the observed Item Facility of the whole cohort, and C and F are constants, predicts the probable Facility for Borderline candidates over the test, in other words, the cut score for Borderline candidates. We describe ways of estimating C and F in any given circumstance, and suggest typical values arising from this particular study: that C = 12.3 and F = 0.021.ConclusionsC and F are relatively stable, and that the equation y = 12.3.e0.021xcan rapidly be applied to the item Facility for every item. The average value represents the cut score for the assessment as a whole. This represents a novel retrospective method based on test takers.Compared to the Cohen method which draws on one score and one candidate, this method draws on all items and candidates in a test. We propose that it can be used to standard set a whole test, or a particular item where the predicted Angoff score is very different from the observed Facility.

Weighted Internal Model Control-Proportional Integral Derivative Control Scheme Via Fractional Gradient Descent Algorithm

An adaptive controller design technique based on internal model control (IMC) scheme is proposed in this paper. Multiple IMC controllers having different values of filter time constants and exhibiting widely different performance are combined via weight update rule. The weight update rule, formulated via convex combination of integral and fractional order gradient descent algorithms, assigns time varying weights to individual candidate controllers to obtain an enhanced performance over the individual candidate controllers. The beauty of the proposed technique is that it employs the simplicity of one degree-of-freedom (1DOF) IMC structure to achieve an improved performance over existing 2DOF control schemes. The efficacy of the proposed technique is demonstrated via three illustrative examples and via experimental validation on the hardware setup of dc servosystem. An extensive comparative analysis in terms of simulation plots and performance indices offers a testimony to the effectiveness of the proposed scheme.

An Inexpensive Retrospective Standard Setting Method Based on Item Facilities

BackgroundStandard setting is one of the most challenging aspects of assessment in high-stakes healthcare settings. The Angoff methodology is widely used, but poses a number of challenges, including conceptualisation of the just-passing candidate, and the time-cost of implementing the method. Cohen methodologies are inexpensive and rapid but rely on the performance of an individual candidate. A new method of standard setting, based on the entire cohort and every item, would be valuable. MethodsWe identified Borderline candidates by reviewing their performance across all assessments in an academic year. We plotted the item scores of the Borderline candidates in comparison with Facility for the whole cohort and fitted curves to the resulting distribution. ResultsWe propose that for any given Item, an equation of the form y ≈ C.eFxwhere y is the Facility of Borderline candidates on that Item, x is the observed Item Facility of the whole cohort, and C and F are constants, predicts the probable Facility for Borderline candidates over the test, in other words, the cut score for Borderline candidates. We describe ways of estimating C and F in any given circumstance, and suggest typical values arising from this particular study: that C = 12.3 and F = 0.021.ConclusionsWe propose that C and F are relatively stable, and that the equation y = 12.3.e0.021xcan rapidly be applied to the item Facility for every item. The average value represents the cut score for the assessment as a whole. This represents a novel retrospective method based on test takers. Compared to the Cohen method which draws on one score and one candidate, this method draws on all items and candidates in a test. It can be used to standard set a whole test, or a particular item where the predicted Angoff score is very different from the observed Facility.

Strategic Split-Ticket Voting in Mixed Electoral Systems

This article aims to examine strategic split-voting in mixed systems by analyzing the results of elections in three countries using mixed electoral systems—Germany, Hungary, and Lithuania—to further improve researchers' understanding of the relationship between strategic voting and ticket splitting. This is achieved by exploring new quantitative measures. The three selected countries do not use identical electoral systems, but their common characteristic is that they provide an opportunity for voters to split their ballot between an individual candidate running in a single-member constituency and a party list. This makes it possible to compare the two different types of votes and to search for patterns indicating strategic behavior. In this article, the authors introduce two analytic tools: one for determining the approximate quantity of split ballots and another for measuring strategic voting patterns based on the concentration of split tickets.

Genetic and molecular characterization of multicomponent resistance of Pseudomonas against allicin

The common foodstuff garlic produces the potent antibiotic defense substance allicin after tissue damage. Allicin is a redox toxin that oxidizes glutathione and cellular proteins and makes garlic a highly hostile environment for non-adapted microbes. Genomic clones from a highly allicin-resistant Pseudomonas fluorescens (PfAR-1), which was isolated from garlic, conferred allicin resistance to Pseudomonas syringae and even to Escherichia coli. Resistance-conferring genes had redox-related functions and were on core fragments from three similar genomic islands identified by sequencing and in silico analysis. Transposon mutagenesis and overexpression analyses revealed the contribution of individual candidate genes to allicin resistance. Taken together, our data define a multicomponent resistance mechanism against allicin in PfAR-1, achieved through horizontal gene transfer.