Consensus Judgment Research Articles

An Illusory Consensus Effect: The Mere Repetition of Information Increases Estimates That Others Would Believe or Already Know It

How do people estimate the prevalence of beliefs and knowledge among others? Here, we examine the hypothesis that mere repetition of information increases such perceptions of consensus — an “illusory consensus effect.” Although existing evidence suggests that repeated exposure to information may increase its perceived consensus, the impact of repetition has not been tested in isolation from other source and contextual cues. We conducted two experiments to fill in this gap. Prolific participants located in the U.S. read a series of trivia claims — half true and half false in Experiment 1 and all true in Experiment 2. These claims were not attributed to any source. After a short delay, participants made consensus judgments about previously seen (repeated) and new trivia claims. Repetition significantly increased perceived consensus in both experiments; in Experiment 1, participants judged that more Americans would believe repeated (vs. new) information, and in Experiment 2, participants judged that more Americans knew repeated (vs. new) information. These findings provide strong evidence for an illusory consensus effect, such that mere exposure to information increases perceptions of two different measures of consensus: how many others would believe it as well as estimates of current public knowledge. These findings are relevant to our understanding of how our information environments may contribute to (mis)perceptions of consensus.

Optimization Strategies for Waterfront Plant Landscapes in Traditional Villages: A Scenic Beauty Estimation–Entropy Weighting Method Analysis

This investigation delves into the waterfront plant landscapes of traditional villages in Western Hunan, China, aiming to bolster sustainable ecological resource management, amplify ecological culture, and ameliorate environmental standards. Furthermore, it endeavors to furnish a theoretical scaffold for the meticulous construction and assessment of these landscapes. This study has illustrated the waterfront botanical landscapes of 32 traditional hamlets within the Xiangxi region, integrating prior research on the waterfront botanical regression model based on the Scenic Beauty Estimation (SBE) method. It established and investigated fifteen landscape factors pivotal to the aesthetic valorization of these village waterfronts. The study concocted a beauty quality evaluation model, unearthing a significant correlation (p < 0.01) across evaluations by students majoring in landscape architecture, expert landscape architects, and laypersons, thus underscoring a consensus in aesthetic judgments. A noteworthy correlation between the beauty value (Z-value) and the entropy weight value was elucidated through the equation EWM = −0.106 + 0.425ZSBE, showcasing the landscape quality’s variance among the studied villages. The formulated evaluation model accentuates the significance of seasonal variation, scale affinity, and a rich hierarchical structure.

Consensus adjustment for multi-attribute group decision making based on cross-allocation

Consensus adjustment is crucial in group decision making (GDM), aiming to reduce discrepancies in decision makers’ (DMs’) judgments for final decision results. The consensus adjustments made by DMs are interactive rather than independent. However, few studies investigate the consensus adjustment problem from the perspective of interactions among DMs. This study first constructs a model to determine the total minimum consensus adjustment under the requirements of consensus threshold and individual-collective judgment bias. Then, a consensus adjustment approach based on cross-allocation scheme is proposed to address the inconsistency between individual and collective minimum adjustments, which concerns all DMs’ individual favorable allocation results under the total minimum consensus adjustment. The cross-allocation scheme ensures unanimous support for the same allocation result among all rational DMs, thereby eliminating the discrepancies among them. Subsequently, the optimization model-based minimum consensus judgment penalty is formulated to handle the non-cooperative behaviors of DMs. Furthermore, we show how to determine the unique consensus adjustment result for the non-cooperative DMs using the cross-allocation scheme. Therefore, our study contributes by developing a new GDM method that conducts consensus adjustment allocation by considering interactions among DMs. Finally, a case study is employed to demonstrate the specific application of the new method and discuss its efficiency. Meanwhile, comparison analysis and simulation experiments are provided.

Determinants of consensus in person judgments: The joint influence of information overlap, information quantity, cross-situational consistency, and shared meaning.

This study investigated the effects and interplay of several core determinants of consensus in person perception: information overlap, information quantity, cross-situational consistency, and shared meaning. Targets (N = 200) were filmed in different standardized situations. Perceivers either watched the same target in different situations (N = 1,395 perceivers) or different targets in the same situation (N = 3,963 perceivers) and then rated the targets' personalities after each video. Overlap of the observed situations was systematically varied across perceivers. Consensus was higher when perceivers (a) observed a target in more overlapping situations, (b) observed a target in more situations overall, judged characteristics (c) for which between-target differences were more consistent across situations, or (d) for which perceivers had more similar meaning systems. The effect of overlap was more important with low consistency or information quantity, but moderate in size overall. In light of prior research failing to adequately operationalize overlap and consider its interplay with other factors, this study presents the strongest evidence to date on these issues. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Variation observed in consensus judgments between pairs of reviewers when assessing the risk of bias due to missing evidence in a sample of published meta-analyses of nutrition research

ObjectivesTo evaluate the risk of bias due to missing evidence in a sample of published meta-analyses of nutrition research using the Risk Of Bias due to Missing Evidence (ROB-ME) tool and determine inter-rater agreement in assessments. Study Design and SettingWe assembled a random sample of 42 meta-analyses of nutrition research. Eight assessors were randomly assigned to one of four pairs. Each pair assessed 21 randomly assigned meta-analyses, and each meta-analysis was assessed by two pairs. We calculated raw percentage agreement and chance corrected agreement using Gwet's Agreement Coefficient (AC) in consensus judgments between pairs. ResultsAcross the eight signaling questions in the ROB-ME tool, raw percentage agreement ranged from 52% to 100%, and Gwet's AC ranged from 0.39 to 0.76. For the risk-of-bias judgment, the raw percentage agreement was 76% (95% confidence interval 60% to 92%) and Gwet's AC was 0.47 (95% confidence interval 0.14 to 0.80). In seven (17%) meta-analyses, either one or both pairs judged the risk of bias due to missing evidence as “low risk”. ConclusionOur findings indicated substantial variation in assessments in consensus judgments between pairs for the signaling questions and overall risk-of-bias judgments. More tutorials and training are needed to help researchers apply the ROB-ME tool more consistently.

Who makes a more consistent first impression? Examining the structure and correlates of dissensus.

How do targets shape consensus in impression formation? Targets are known to play an outsized role in the accuracy of first impressions, but their influence on consensus has been difficult to study. With the help of the recently developed extended Social Relations Model, we explore the structure and correlates of individual differences in consensus (i.e., dissensus). Across 3 studies, 187 photographs of targets were rated by 960 perceivers on personality and evaluative traits, as well as being coded for physical cues by trained coders. We explored the within-target consistency of consensus across traits, as well as its relationship to four categories of theoretically relevant correlates: expressiveness, normativity, positivity, and social categories. The tendency to make a consistent impression on others was broadly consistent across traits. High-consensus targets tended to be more expressive, had more normative physical cues, and were viewed more positively. At least in a first impression context, targets may play a unique role in predicting the consensus of personality judgments by providing perceivers with more information to work with, and making a negative impression on others may carry social costs.

A novel extension of Pythagorean fuzzy MULTIMOORA approach for new product development

This study explores how to enhance the decision-making processes in the phases of idea generation or alternative selection during the new product development (NPD) process. NPD is acknowledged as the central function of businesses in an increasingly competitive marketplace. In the current era, the highly uncertain and rapidly changing market environment makes the NPD extremely vague and complex. To be able to find a suitable solution to this complexity, the proposed research aims to categorize the decision points in the process of NPD regarding software development and identify the fuzziness elements affecting the process. The goal of a decision-making process is to prioritize several alternatives with respect to some required objectives and to select the best among them. Multi-Criteria Decision-Making (MCDM) may support reaching a consensus judgment with the collective assessment of Decision Makers (DMs). We introduce a novel evaluation approach for this problem. The proposed approach employs a MULTIMOORA (Multi-objective Optimization by Ratio Analysis plus the Full Multiplicative Form) MCDM technique under Pythagorean Fuzzy Sets (PFSs) objective world environment to cope with an ambiguous environment using Group Decision Making (GDM) setting to shape the decisions. The PFSs have demonstrated their advantages in dealing with vagueness and uncertainty over crisp, fuzzy, or intuitionistic fuzzy sets. Therefore, PFSs can represent the DMs’ judgments and preferences in a better structure, ensuring enhanced decision-making in a group consensus. A case study on gaming software and app development is presented to validate the functionality of the proposed method. The results are compared and assessed with the help of a sensitivity analysis. This research makes a real contribution to the literature by proposing a novel evaluation method to rate and select NPD (gaming software and apps) to deal with the inexactness and vagueness associated with the criteria and alternatives.

How Do Investor and Auditor Materiality Judgments Compare?

SUMMARY Materiality remains a challenging concept for auditors to implement in practice. The challenges underlying auditor materiality assessments are compounded by the fact that materiality is typically defined from the investor’s (rather than the auditor’s) perspective. Despite this investor orientation, there is little empirical evidence about investors’ materiality judgments, specific quantitative and qualitative factors underlying their judgments, and how their judgments compare to auditors who implement materiality in practice. This article summarizes a recent study by DeZoort, Holt, and Stanley (2019) that addresses this problem by modeling sophisticated and unsophisticated investors’ materiality judgments in a policy-capturing study, using experienced auditors as a benchmark. Results indicate significant differences in materiality judgments, judgment consensus, and cue utilization among the three participant groups. Findings also reveal between-group differences in self-reported quantitative materiality thresholds, judgment self-insight, as well as judgment confidence. We conclude the article with a discussion of the practical implications surrounding these findings.

Epistemic motivation facilitates advice seeking and utilization by groups

AbstractDrawing on a motivated information processing model, we tested the hypothesis that groups' receptivity to outside advice is facilitated by their epistemic motivation—the desire to gain an accurate understanding of the world. Epistemic motivation was measured by proxy in Study 1 using a team task reflexivity measure, and was experimentally manipulated in Studies 2 and 3 by varying, respectively, either the amount of time allotted to complete the task or whether a consensus judgment was required before receiving advice. Receptivity to advice was operationalized as group advice seeking in Studies 1 and 2, and as advice utilization in Study 3. In support of our hypothesis, groups with higher levels of epistemic motivation consistently sought out and utilized advice more than those with lower levels of epistemic motivation. Moreover, epistemic motivation affected judgment accuracy via groups' receptivity to advice.

Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs.

Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the concordance of expert-determined standards with a clinical gold standard (herein, pathological confirmation) and the effects of different expert-determined reference standards on the estimates of radiologists' diagnostic performance to detect malignant pulmonary nodules on chest radiographs with and without the assistance of a DLAD model. This study included chest radiographs from 50 patients with pathologically proven lung cancer and 50 controls. Five expert-determined standards were constructed using the interpretations of 10 experts: individual judgment by the most experienced expert, majority vote, consensus judgments of two and three experts, and a latent class analysis (LCA) model. In separate reader tests, additional 10 radiologists independently interpreted the radiographs and then assisted with the DLAD model. Their diagnostic performance was estimated using the clinical gold standard and various expert-determined standards as the reference standard, and the results were compared using the t test with Bonferroni correction. The LCA model (sensitivity, 72.6%; specificity, 100%) was most similar to the clinical gold standard. When expert-determined standards were used, the sensitivities of radiologists and DLAD model alone were overestimated, and their specificities were underestimated (all p-values < 0.05). DLAD assistance diminished the overestimation of sensitivity but exaggerated the underestimation of specificity (all p-values < 0.001). The DLAD model improved sensitivity and specificity to a greater extent when using the clinical gold standard than when using the expert-determined standards (all p-values < 0.001), except for sensitivity with the LCA model (p = 0.094). The LCA model was most similar to the clinical gold standard for malignant pulmonary nodule detection on chest radiographs. Expert-determined standards caused bias in measuring the diagnostic performance of the artificial intelligence model.

Social network group decision-making for probabilistic linguistic information based on GRA

In group decision-making problems, decision-makers typically use probabilistic linguistic term sets (PLTSs) to express their evaluation opinions. This paper focuses on the social network group decision-making method for probabilistic linguistic information. First, we propose a new consensus judgment mechanism by computing the absolute grey relation degree between the most probable optimal vectors of individual decision makers and collective opinion. Furthermore, in order to reduce the calculated amount in the decision-making process, we propose a model to transform the score value into a PLTS. This technique uses stochastic multicriteria acceptability analysis to determine the criteria weights. The preferences of the decision-makers can be accurately portrayed by this approach. In addition, we put forward a model to transform the score value into a PLTS and propose a new way to obtain the criteria weights using stochastic multicriteria acceptability analysis. Moreover, we develop an advice generation method with two steps for the PLTS in a feedback adjustment process. Finally, we use a case study and comparative analysis to illustrate the effectiveness of our method. Our proposed method can be applied to address many group decision-making problems involving multiple interest groups, such as social policy, facility placement, and other issues.

The Practice of Quality Assessment Standard Development for an Architectural Work in Thailand

This study explores the quality assessment standards of practice to develop guidelines for high-rise building and housing construction architectural work. An internal wall construction works currently unclear on quality acceptance between involved stakeholders is focused on this research. To achieve this, literature is reviewed on the construction quality assessment systems, the quality assessment guidelines, and the specifications that are currently in place. In this research, a Delphi method is employed to achieve a reliable consensus of subjective judgment and conducted on fifteen purposive experts, who are from the following organizations: Department of Public Works and Town &amp; Country Planning, The Engineering Institute of Thailand, The Association of Siamese Architects, private building developers, building construction consultants and building contractors. A semi-structured interview comprised of open-ended questions is conducted in Round 1. Questionnaires are used in Rounds 2 and 3. The findings indicate that criteria of wall inspection, standards and guidelines, measurement methods, and tools should help develop national standards of practice as a pilot guideline for the quality inspection on interior wall work of high-rise buildings in Thailand. These valuable results also lead to new product development for a measurement tool invention in the ongoing research.

ЦЕННОСТНОЕ ИЗМЕРЕНИЕ ПУБЛИЧНОЙ ПОЛИТИКИ

The paper discusses the formation of the theory of public values, determines its capabilities and limitations in creating a valid tool for the value measurement of decisions made in the public space. The request for such an instrument was formed both by civil society structures, fearful of the substitution of the real interests of citizens by the interests of the elite strata, and by state bodies seeking to estimate the reaction of society to managerial initiatives. The theory of public values arises on a controversial methodological foundation, which is primarily reflected in the ambiguous interpretation of the very concept of «public value». Firstly, as a special type of value of public goods produced in the public space. Secondly, as consensus judgments about the desired ways of organizing public life, thirdly, as the relationship of people to external social objects, which develops in the course of satisfying their basic needs. The pluralism of scientific interpretation creates difficulties in creating a universal way of value measurement of public policy, since each theoretical model involves its own ways of operationalizing the basic concepts and a contradictory set of indicators. Two methods of measuring the public value of decisions are considered: «public value mapping» (PVM) and «public value scorecard» (PVSC). The differences between these methods are due to the initial methodological principles that determine the subject orientation of the research procedures used. In the first case, we are talking about establishing the degree of compliance of decisions made with consensus public values, in the second case, about identifying the subjective attitude of citizens to specific public decisions. It is noted that in the scientific community an active search for criteria for assessing the public value of government decisions is accompanied by restrained optimism. It is recognized that it is easier for specialists to determine the public value of a particular solution but attempts to create a universal toolkit are more than modest.

Consensual and idiosyncratic trustworthiness perceptions independently influence social decision‐making

AbstractTrustworthiness perceptions are based on facial features that are seen as trustworthy by most people (e.g., resemblance to a smile) and features that are only seen as trustworthy by a specific perceiver (e.g., resemblance to a loved one). In other words, trustworthiness perceptions reflect consensual and idiosyncratic judgment components. Yet, when examining the influence of facial cues on social decision‐making previous studies have almost exclusively focused on consensual judgments, ignoring the potential role of idiosyncratic judgments. Results of two studies, with 491 participants making 15,656 trust decisions, showed that consensual and idiosyncratic trustworthiness judgments independently influenced participants’ likelihood to trust an interaction partner, with no significant differences in the magnitude of the effects. These results highlight the need to consider both consensual and idiosyncratic judgments. Previous work, which only focused on the effect of consensual judgments, may have underestimated the overall influence of trustworthiness perceptions on social decision‐making.

Speech-Language Pathologists' Ratings of Speech Accuracy in Children With Speech Sound Disorders.

Forming accurate and consistent speech judgments can be challenging when working with children with speech sound disorders who produce a large number and varied types of error patterns. Rating scales offer a systematic approach to assessing the whole word rather than individual sounds. Thus, these scales can be an efficient way for speech-language pathologists (SLPs) to monitor treatment progress. This study evaluated the interrater reliability of an existing 3-point rating scale using a large group of SLPs as raters. Utilizing an online platform, 30 SLPs completed a brief training and then rated single words produced by children with typical speech patterns and children with speech sound disorders. Words were closely balanced across the three rating categories of the scale. The interrater reliability of the SLPs ratings to a consensus judgment was examined. The majority of SLPs (87%) reached substantial interrater reliability to a consensus judgment using the 3-point rating scale. Correct productions had the highest interrater reliability. Productions with extensive errors had higher agreement than those with minor errors. Certain error types, such as vowel distortions, were especially challenging for SLPs to judge. This study demonstrated substantial interrater reliability to a consensus judgment among a large majority of 30 SLPs using a 3-point rating. The clinical implications of the findings are discussed along with proposed modifications to the training procedure to guide future research.

Measuring the sustainability of beef supply chain with rapid appraisal for beef supply chain

Background and Aim:Nationally, there has always been a gap between the demand for beef and its supply, although supply growth is proportional with demand growth and even exceeds it in some regions in Indonesia. This research study aims to measure the sustainability status of the beef supply chain and applies the developed measurement system to a specific beef supply chain by identifying suitable indicators and their scale. Moreover, this research study provides some recommendations for the improvement of the sustainability status of the beef supply chain.Materials and Methods:In this research study, 11 and nine indicators were analyzed to assess the sustainability status of the beef supply chain at the farm and slaughterhouse chain levels. A rapid appraisal for beef supply chain was applied to rapidly assess the sustainability status of beef supply chains using Multidimensional Scaling (MDS). The Delphi method was utilized as an iterative process to collect data and obtain consensus of experts’ judgments regarding the policies that should be implemented to improve the most sensitive indicator affecting the economic, social, and environmental dimensions.Results:Analysis of ordination with MDS shows the regional sustainability index value for multidimensional approaches of beef cattle farms and beef slaughterhouses. The sustainability index value for beef cattle farms was 56.14 (moderately sustainable), 48.02 (fairly unsustainable), and 48.77 (fairly unsustainable) in Semarang, Sragen, and Boyolali, respectively. Moreover, the sustainability index value for beef slaughterhouses was 47.05 (fairly unsustainable), 54.83 (moderately sustainable), and 54.19 (moderately sustainable) in Semarang, Sragen, and Boyolali, respectively. Policy recommendation was focused on the basis of the results of leverage analysis, which highlighted the most indicative factor affecting sustainability for each dimension.Conclusion:Measurement results revealed that the achievement of beef supply chain sustainability requires targeted efforts through the deployment of several policies as the current status of sustainability in beef farms and beef slaughterhouses was only inclined toward moderately sustainable and fairly unsustainable. Although all the surveyed regions in this study can meet the regional needs of beef meat on their own and even distribute the excess to other regions, none of the beef supply chains of the surveyed region indicated good sustainability.

Ontario's COVID-19 Modelling Consensus Table: mobilizing scientific expertise to support pandemic response.

SettingCOVID-19 has highlighted the need for credible epidemiological models to inform pandemic policy. Traditional mechanisms of commissioning research are ill-suited to guide policy during a rapidly evolving pandemic. At the same time, contracting with a single centre of expertise has been criticized for failing to reflect challenges inherent in specific modelling approaches.InterventionThis report describes an alternative approach to mobilizing scientific expertise. Ontario’s COVID-19 Modelling Consensus Table (MCT) was created in March 2020 to enable rapid communication of credible estimates of the impact of COVID-19 and to accelerate learning on how the disease is spreading and what could slow its transmission. The MCT is a partnership between the province and academic modellers and consists of multiple groups of experts, health system leaders, and senior decision-makers. Armed with Ministry of Health data, the MCT meets once per week to share results from modelling exercises, generate consensus judgements of the likely future impact of COVID-19, and discuss decision-makers’ priorities.OutcomesThe MCT has enabled swift access to data for participants, a structure for developing consensus estimates and communicating these to decision-makers, credible models to inform health system planning, and increased transparency in public reporting of COVID-19 data. It has also facilitated the rapid publication of research findings and its incorporation into government policy.ImplicationsThe MCT approach is one way to quickly draw on scientific advice outside of government and public health agencies. Beyond speed, this approach allows for nimbleness as experts from different organizations can be added as needed. It also shows how universities and research institutes have a role to play in crisis situations, and how this expertise can be marshalled to inform policy while respecting academic freedom and confidentiality.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021.

There exist differences in the epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selections between gastric cancer patients from the Eastern and Western countries. The Chinese Society of Clinical Oncology (CSCO) has organized a panel of senior experts specializing in all sub‐specialties of gastric cancer to compile a clinical guideline for the diagnosis and treatment of gastric cancer since 2016 and renews it annually. Taking into account regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted expert consensus judgment on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes in China. The 2021 CSCO Clinical Practice Guidelines for Gastric Cancer covers the diagnosis, treatment, follow‐up, and screening of gastric cancer. Based on the 2020 version of the CSCO Chinese Gastric Cancer guidelines, this updated guideline integrates the results of major clinical studies from China and overseas for the past year, focused on the inclusion of research data from the Chinese population for more personalized and clinically relevant recommendations. For the comprehensive treatment of non‐metastatic gastric cancer, attentions were paid to neoadjuvant treatment. The value of perioperative chemotherapy is gradually becoming clearer and its recommendation level has been updated. For the comprehensive treatment of metastatic gastric cancer, recommendations for immunotherapy were included, and immune checkpoint inhibitors from third‐line to the first‐line of treatment for different patient groups with detailed notes are provided.

Validation of a Clinical Decision Rule to Predict Abuse in Young Children Based on Bruising Characteristics

Bruising caused by physical abuse is the most common antecedent injury to be overlooked or misdiagnosed as nonabusive before an abuse-related fatality or near-fatality in a young child. Bruising occurs from both nonabuse and abuse, but differences identified by a clinical decision rule may allow improved and earlier recognition of the abused child. To refine and validate a previously derived bruising clinical decision rule (BCDR), the TEN-4 (bruising to torso, ear, or neck or any bruising on an infant <4.99 months of age), for identifying children at risk of having been physically abused. This prospective cross-sectional study was conducted from December 1, 2011, to March 31, 2016, at emergency departments of 5 urban children's hospitals. Children younger than 4 years with bruising were identified through deliberate examination. Statistical analysis was completed in June 2020. Bruising characteristics in 34 discrete body regions, patterned bruising, cumulative bruise counts, and patient's age. The BCDR was refined and validated based on these variables using binary recursive partitioning analysis. Injury from abusive vs nonabusive trauma was determined by the consensus judgment of a multidisciplinary expert panel. A total of 21 123 children were consecutively screened for bruising, and 2161 patients (mean [SD] age, 2.1 [1.1] years; 1296 [60%] male; 1785 [83%] White; 1484 [69%] non-Hispanic/Latino) were enrolled. The expert panel achieved consensus on 2123 patients (98%), classifying 410 (19%) as abuse and 1713 (79%) as nonabuse. A classification tree was fit to refine the rule and validated via bootstrap resampling. The resulting BCDR was 95.6% (95% CI, 93.0%-97.3%) sensitive and 87.1% (95% CI, 85.4%-88.6%) specific for distinguishing abuse from nonabusive trauma based on body region bruised (torso, ear, neck, frenulum, angle of jaw, cheeks [fleshy], eyelids, and subconjunctivae), bruising anywhere on an infant 4.99 months and younger, or patterned bruising (TEN-4-FACESp). In this study, an affirmative finding for any of the 3 BCDR TEN-4-FACESp components in children younger than 4 years indicated a potential risk for abuse; these results warrant further evaluation. Clinical application of this tool has the potential to improve recognition of abuse in young children with bruising.

성범죄에 있어 결과발생과 불능미수 성립에 관한 소고 -대법원 2019. 3. 28. 선고 2018도16002 전원합의체 판결을 중심으로

성범죄에 있어 결과발생과 불능미수 성립에 관한 소고 -대법원 2019. 3. 28. 선고 2018도16002 전원합의체 판결을 중심으로