Difficult Questions Research Articles

Children, juveniles, and crime in early modern London: Old Bailey trials, 1674–1750

Abstract This article uses the early records of the Old Bailey to examine how the court handled cases involving children and juveniles, whether as offenders, victims or witnesses. It argues that though juvenile courts belong to a later age, the early modern court was already applying different criteria in trying young offenders. It demonstrates how juries used age, gender and related considerations to justify the ‘pious perjury’ that sheltered many from the full rigour of the law. Previous work on children as victims has focused on child-rape and infanticide. This article explores other categories. It argues that in cases of death following a severe beating the court's sympathies lay firmly with the defendants, determined to uphold the authority of employers and parents. Lastly, the article explores cases involving children as witnesses, which raised difficult questions about the admissibility of evidence. Judges had to decide if the youngster was sufficiently mature to give evidence on oath.

Kenstituent power: an exploration of feminist constitutional change in Barbie

Greta Gerwig’s Barbie explores the influence of childhood dream worlds and toys over adult life, and the singular importance of a toy which represents an empowered woman. But this story plays out against the backdrop of deep societal challenges. That the subject matter of the film is light does not detract from its cultural significance; it enhances its reach and thereby its influence. Constitutional change, property, dissent, inequality and revolution are not the B-plot of the film, they suffuse every scene and motivate its major characters. In this article we explore the significance of Barbie Land as a supposed embodiment of a feminist utopia and the extent to which Gerwig is confronting viewers with difficult questions about authority and just governance in the Real World.

What does religion have to do with it: Exploring noninstitutional arguments for effective enforcement of IPR

AbstractThrough this paper the authors intend to establish a connect between religion and Intellectual Property Rights (IPR) particularly how various religions have justified IPRs and analyze whether religion can prove to be the much‐needed enforcement tool to fight infringement of IPRs. Intellectual Property is a domain which is governed purely by creativity and technology and has traditionally been justified by utilitarianism. However, the evidence we are in possession of does not entirely justify the rationale of exclusive rights granted under the current IPR regime. While questioning the contradictory evidence seems as a logical move, instead scholars are turning to nonindustrial faith‐based arguments which justify intellectual property as a moral end in itself. A growing number of academics are choosing to devote at least a portion of their research to examining how religious thought can influence approaches to difficult intellectual property questions because they find the religious texts to be a rich source of inspiration on both temporal and eternal issues. A major obstacle in the enforcement of IPR is that people are not entirely convinced that infringing IPR is unethical. This enforcement challenge, surprisingly in the presence of legislations, may be tackled by informal institutions such as religious commitments.

What does it mean to be?

This paper explores the value of career coaches asking philosophical questions, specifically relating to existentialism, in order to enhance clients’ self-awareness, goal-setting, and decision-making. It argues that existential concepts, such as authenticity and essence, could potentially serve as valuable additions to a coach’s toolkit to help stimulate, challenge and shift forwards a client’s thinking when faced with difficult career-related questions. Existentialism’s potential value is explored in relation to three established career coaching models – the GROW model, the OSKAR model, and the Skilled Helper model.

Challenging Long-Held Best Practices, Offering New Insights Into Established Beliefs, and Asking Difficult Questions

Challenging Long-Held Best Practices, Offering New Insights Into Established Beliefs, and Asking Difficult Questions

Large language models in pathology: A comparative study of ChatGPT and Bard with pathology trainees on multiple-choice questions

Large language models (LLMs), such as ChatGPT and Bard, have shown potential in various medical applications. This study aimed to evaluate the performance of LLMs, specifically ChatGPT and Bard, in pathology by comparing their performance with those of pathology trainees, and to assess the consistency of their responses. We selected 150 multiple-choice questions from 15 subspecialties, excluding those with images. Both ChatGPT and Bard were tested on these questions across three separate sessions between June 2023 and January 2024, and their responses were compared with those of 16 pathology trainees (8 junior and 8 senior) from two hospitals. Questions were categorized into easy, intermediate, and difficult based on trainee performance. Consistency and variability in LLM responses were analyzed across three evaluation sessions. ChatGPT significantly outperformed Bard and trainees, achieving an average total score of 82.2% compared to Bard's 49.5%, junior trainees' 45.1%, and senior trainees' 56.0%. ChatGPT's performance was notably stronger in difficult questions (63.4%–68.3%) compared to Bard (31.7%–34.1%) and trainees (4.9%–48.8%). For easy questions, ChatGPT (83.1%–91.5%) and trainees (73.7%–100.0%) showed similar high scores. Consistency analysis revealed that ChatGPT showed a high consistency rate of 80%–85% across three tests, whereas Bard exhibited greater variability with consistency rates of 54%–61%. While LLMs show significant promise in pathology education and practice, continued development and human oversight are crucial for reliable clinical application.

Development of Essential Thinking Test Instrument using the Presseisen Taxonomy on Ecosystem Material for Grade X High School Students

The test instrument is a measuring tool in the assessment process used to obtain information in the form of data on student learning outcomes, both cognitive aspects and thinking skills. The use of test instrument to measure students' thinking skills is still rarely used. This study aims to develop an essential thinking test instrument using the Presseisen taxonomy on valid and reliable ecosystem material. This research uses the Research Development (RD) method with the 3D modified development model combined with the test development stages consisting of 6 stages. Data collection in this research was carried with interviews, tests, and test instrument validation sheets. The analysis included content validity analysis, interrater reliability, and Rasch model analysis. The results showed that all items were valid based on content validity. Interrater reliability has a value of 0.783 with a good category. All items are declared fit, but item number 7 contains bias so it needs to be discarded. Cronbach's alpha has a value of 0.68 in the enough category, person reliability has a value of 0.50 in the weak category, and item reliability has a value of 0.99 in the excellent category. The item difficulty level group consists of 2 very difficult questions, 4 difficult questions, 2 easy questions, and 2 very easy questions. Based on the result of the research, it can be concluded that there are 9 items that are declared valid and reliable for use.

On the political ontology of making things up in political ecology critique: Responding to Bormpoudakis (2019) and Knudsen (2023)

I engage with two recent articles published in the Journal of Political Ecology, both of which critique political ecology engagements with ontological and epistemological complexities. These complexities might be distilled into the idea that how 'the world' is socially known also shapes how the world is known to be. I explore three key issues worked through in these papers, partly with reference to work of mine, namely: 1) conservation struggles around biodiversity offsetting; 2) debates regarding plural and relational ontologies, particularly representations of 'flatness' and 'depth' in ontological considerations; and 3) critical realism, specifically distinctions between perspectives on transitive and intransitive dimensions in qualifying understandings of reality. I highlight a pernicious problem of dismissive approaches towards analysts trying to ask difficult and subtle questions about 'onto-epistemology.' This situation seems surprising given the effort in political ecology towards recognising and respecting plural knowledges, particularly knowledges often overridden by discourses emboldened by structures of power. My overall aim is towards clarity in ongoing political ecology debate on these issues, alongside the pursuit of respectful praxis in this burgeoning area of engagement.

Deciding Difficult Questions of Professional Ethics: A Model of Nuanced Decision-Making

Deciding Difficult Questions of Professional Ethics: A Model of Nuanced Decision-Making

The production and utility of evidence synthesis during the COVID-19 pandemic in Canada: perspectives of evidence synthesis producers

Background: COVID-19 accentuated an evergreen dilemma in evidence-informed policy making: the imperative to synthesise the best available evidence with limited time to produce high quality synthesis. The pandemic prompted the adaptation of evidence synthesis practices to match the urgency of the crisis, and heightened demand by policy makers, while maintaining a focus on quality. This study documents the response to these challenges from the perspectives of those who produced evidence syntheses in Canada. Methods: A qualitative phenomenological study was conducted between October 2022 and January 2023. Data collection included interviews with 22 participants within 19 organisations across seven provinces. A thematic analysis was performed and reported narratively. Results: Evidence synthesis producers in Canada adapted in response to the demands of different types of requests during the pandemic. Participants described several key challenges in responding to end-users, in which a lack of knowledge of evidence synthesis processes and products prompted difficult questions and unrealistic expectations. They responded to the needs of evidence synthesis requestors by creating custom syntheses, utilising rapid review methodologies, emphasising limitations and incorporating recommendations into syntheses. Discussion and conclusion: The evidence synthesis field was able to adapt to pandemic challenges in valuable ways. Still, this experience accentuates disconnects between producers and users, including differing views on the purpose, methods, limitations and implementation of synthesis findings.

The future of tourism: an interview with Dr Daniel Wright about the genre of science fiction

PurposeAs the Journal of Tourism Futures celebrates its 10th Anniversary, Dr Ian Yeoman (Hotel Management School Leeuwarden) interviews Dr Daniel Wright (University of Central Lancashire) about the future genre of science fiction and his publications.Design/methodology/approachA personal interview.FindingsScience fiction research is about asking difficult questions, the questions we feel uncomfortable asking and answering. Science fiction is a powerful medium to imagine the future, which students love as it is provocative. In the interview, Dr Wright reflects upon his own writing from immortality to the end of the world.Originality/valueThe power of science fiction, as a genre of transformation, skepticism and thinking out of the box, is often missing in futures studies and scenario planning.

An analysis of the Crossbred Algorithm for the MQ Problem

The Crossbred algorithm is currently the state-of-the-art method for solving overdetermined multivariate polynomial systems over 𝔽 2 . Since its publication in 2017, several record breaking implementations have been proposed and demonstrate the power of this hybrid approach. Despite these practical results, the complexity of this algorithm and the choice of optimal parameters for it are difficult open questions. In this paper, we prove a bivariate generating series for potentially admissible parameters of the Crossbred algorithm.

Meningkatkan Mutu Evaluasi Pembelajaran: Analisis Soal Pilihan Ganda Bahasa Arab

<p style="text-align: justify;">Learning evaluation is one part of the learning process. Through evaluation, a teacher can find out students' abilities and understanding of the material they have studied. Evaluation instruments require quality tests or questions in terms of validity, reliability, level of difficulty, distinguishing power and effectiveness of distractors. Question items prepared by a teacher to test students' abilities must be recommended to be tested for suitability based on these aspects so that the instruments that have been prepared can be used according to their function. This research was conducted using a descriptive methodology and quantitative research form. The research instrument used was 15 grade 5 PAS Arabic multiple choice questions and the research subjects were 5th grade students at SDIT Al Inayah for the 2023-2024 academic year who were tested by 37 participants. The results of the analysis of the questions in this study in the validity aspect were still not good because only 3 questions (20%) were valid. Then, in terms of the level of difficulty, it is sufficient but not yet balanced because no difficult questions were found. From the aspect of discriminating power, the questions studied were quite good and produced a discriminating power of each question which was 40% and good, reaching 33%. The effectiveness of the distractors in this study was also sufficient because 25% of the distractors were found to be functional, and 25% were rejected. Thus, from the results of this analysis, a teacher can improve and develop question items that are still not good in some of these aspects.</p>

Larger and more instructable language models become less reliable.

The prevailing methods to make large language models more powerful and amenable have been based on continuous scaling up (that is, increasing their size, data volume and computational resources1) and bespoke shaping up (including post-filtering2,3, fine tuning or use of human feedback4,5). However, larger and more instructable large language models may have become less reliable. By studying the relationship between difficulty concordance, task avoidance and prompting stability of several language model families, here we show that easy instances for human participants are also easy for the models, but scaled-up, shaped-up models do not secure areas of low difficulty in which either the model does not err or human supervision can spot the errors. We also find that early models often avoid user questions but scaled-up, shaped-up models tend to give an apparently sensible yet wrong answer much more often, including errors on difficult questions that human supervisors frequently overlook. Moreover, we observe that stability to different natural phrasings of the same question is improved by scaling-up and shaping-up interventions, but pockets of variability persist across difficulty levels. These findings highlight the need for a fundamental shift in the design and development of general-purpose artificial intelligence, particularly in high-stakes areas for which a predictable distribution of errors is paramount.

Utilizing Data Mining Techniques to Predict Student Academic Performance

During this epidemic, a problem in fundamental education affecting all globe is occurring, and we note that education and learning were online and conducted in students. Academic performance of students must be forecast, so that the instructor may better identify the missing pupils and offer teachers a proactive opportunity to develop additional resources for the student to maximize their chances of graduation. Students' academic achievement in higher learning (EH) has been extensively studied in addressing academic inadequacies, rising drop-out rates, graduation delays, and other difficult questions. Simply said, the performance of students refers to the amount to which short and long-term educational objectives are met. Academics nonetheless judge student achievement from different viewpoints, from grades, average grade points (GPAs) to prospective jobs. The literature encompasses numerous computing attempts to improve student performance in schools and colleges, primarily through data mining and analysis learning. However, the efficiency of current smart techniques and models is still unanimous.

Philosophy in prison

The UK prison system is in crisis: overcrowded, understaffed, ill fitted to whatever purpose imprisonment might be intended to have. Prison education is particularly under pressure, especially since a majority of prisoners are functionally illiterate. The charity Philosophy in Prison seeks to address the complex problems of prison education by offering philosophical conversations in prisons: oral, so accessible to most, but driven by difficult philosophical questions that are puzzling to anyone. This process faces down the disadvantage suffered by many within the criminal justice system, that their voices are not heard (the problem of epistemic injustice). For these conversations have an equalising effect, since the problems they address are puzzling to anyone, whether new to it or expert. That general puzzlement allows the participant both to see the viewpoints of others, and to have their own viewpoint seen by others. This matters: it shows each prisoner that they do have standing, in themselves, after all. (This article is published in the thematic collection ‘The arts and humanities: rethinking value for today—views from Fellows of the British Academy’, edited by Isobel Armstrong.)

A heterogeneous continuous age-structured model of mumps with vaccine

In classical mumps models, individuals are generally assumed to be uniformly mixed (homogeneous), ignoring population heterogeneity (preference, activity, etc.). Age is the key to catching mixed patterns in developing mathematical models for mumps. A continuous heterogeneous age-structured model for mumps with vaccines has been developed in this paper. The stability of age-structured models is a difficult question. An explicit formula of R0 was defined for the various mixing modes (isolation, proportional and heterogeneous mixing) with or without the vaccine. The results show that the endemic steady state is unique and locally stable if R0 > 1 without any additional conditions. A number of numerical examples are given to support the theory.

The creative agency of large language models: a philosophical inquiry

AbstractThis paper explores the difficult question of whether Large Language Models (LLMs) are intrinsically creative. Because they can independently create original content, LLMs are often seen as creative agents. Contrary to the belief that LLMs are creative, this paper argues that LLMs are not creative for two reasons. First, LLMs are not creative because they lack an essential component of creativity, which is the first-person experience of the world. Secondly, LLMs are not creative because they are not the principal authors of their creative output, for they lack the subjective awareness and intentionality necessary to be regarded as authors, and their output is a collaborative effort of the AI model, data providers, and other stakeholders. Since they are not full-fledged authors in a traditional sense, they are not creative.

Error Management Training and Adaptive Expertise in Learning Computed Tomography Interpretation

Adaptive expertise helps physicians apply their skills to novel clinical cases and reduce preventable errors. Error management training (EMT) has been shown to improve adaptive expertise with procedural skills; however, its application to cognitive skills in medical education is unclear. To evaluate whether EMT improves adaptive expertise when learning the cognitive skill of head computed tomography (CT) interpretation. This 3-arm randomized clinical trial was conducted from July 8, 2022, to March 30, 2023, in 7 geographically diverse emergency medicine residency programs. Participants were postgraduate year 1 through 4 emergency medicine residents masked to the hypothesis. Participants were randomized 1:1:1 to a difficult EMT, easy EMT, or error avoidance training (EAT) control learning strategy for completing an online head CT curriculum. Both EMT cohorts received no didactic instruction before scrolling through head CT cases, whereas the EAT group did. The difficult EMT cohort answered difficult questions about the teaching cases, leading to errors, whereas the easy EMT cohort answered easy questions, leading to fewer errors. All 3 cohorts used the same cases. The primary outcome was a difference in adaptive expertise among the 3 cohorts, as measured using a head CT posttest. Secondary outcomes were (1) differences in routine expertise, (2) whether the quantity of errors during training mediated differences in adaptive expertise, and (3) the interaction between prior residency training and the learning strategies. Among 212 randomized participants (mean [SD] age, 28.8 [2.0] years; 107 men [50.5%]), 70 were allocated to the difficult EMT, 71 to the easy EMT, and 71 to the EAT control cohorts; 150 participants (70.8%) completed the posttest. The difficult EMT cohort outperformed both the easy EMT and EAT cohorts on adaptive expertise cases (60.6% [95% CI, 56.1%-65.1%] vs 45.2% [95% CI, 39.9%-50.6%], vs 40.9% [95% CI, 36.0%-45.7%], respectively; P < .001), with a large effect size (η2 = 0.19). There was no significant difference in routine expertise. The difficult EMT cohort made more errors during training than the easy EMT cohort. Mediation analysis showed that the number of errors during training explained 87.2% of the difficult EMT learning strategy's effect on improving adaptive expertise (P = .01). The difficult EMT learning strategy was more effective in improving adaptive expertise for residents earlier in training, with a large effect size (η2 = 0.25; P = .002). In this randomized clinical trial, the findings show that EMT is an effective method to develop physicians' adaptive expertise with cognitive skills. ClinicalTrials.gov Identifier: NCT05284838.

Intrinsic Properties and the Problem of “Other Things”

ABSTRACTIntrinsic properties are those which cannot be had or lacked in virtue of other things. Being a square is intrinsic, in this sense, whereas being next to a square is not. But what, exactly, counts as an “other thing” in this context? As it turns out, this is a surprisingly difficult question. I provide a critical assessment of three existing proposals (in terms of identity, mereology, and ontology), before developing my own, alternative account. Along the way, we highlight ways in which this project intersects with other philosophical issues, including debates over the nature of existence, the essentiality of origins, and the truth of priority monism.