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Bernoulli’s 1713 golden theorem is viewed retrospectively in the context of modern model-based frequentist inference that revolves around the concept of a prespecified statistical model M θ (x), defining the inductive premises of inference. It is argued that several widely-accepted claims relating to the golden theorem and frequentist inference are either misleading or erroneous: (a) Bernoulli solved the problem of inference ‘from probability to frequency’, and thus (b) the golden theorem cannot justify an approximate Confidence Interval (CI) for the unknown parameter θ, (c) Bernoulli identified the probability P (A) with the relative frequency 1 n ∑ k = 1 n x k of event A as a result of conflating f (x₀|θ) with f (θ|x₀), where x₀ denotes the observed data, and (d) the same ‘swindle’ is currently perpetrated by the p value testers. In interrogating the claims (a)–(d), the paper raises several foundational issues that are particularly relevant for statistical induction as it relates to the current discussions on the replication crises and the trustworthiness of empirical evidence, arguing that: [i] The alleged Bernoulli swindle is grounded in the unwarranted claim θ̂n (x₀) ≃ θ*, for a large enough n, where θ̂n (X) is an optimal estimator of the true value θ* of θ. [ii] Frequentist error probabilities are not conditional on hypotheses (H₀ and H₁) framed in terms of an unknown parameter θ since θ is neither a random variable nor an event. [iii] The direct versus inverse inference problem is a contrived and misplaced charge since neither conditional distribution f (x₀|θ) and f (θ|x₀) exists (formally or logically) in model-based (M θ (x)) frequentist inference.

Objectives: The rapidly rising incidence of plagiarism among students at universities throughout the world requires attention. This study aimed to determine the extent to which medical and nursing students in Erbil, Iraq, plagiarise, their knowledge, understanding and perceptions of plagiarism and the underlying factors that may lead them to plagiarise. Methods: This cross-sectional study was carried out between January and June 2017 among a sample of 400 undergraduate medical and nursing students at Hawler Medical University in Erbil. Plagiarism-related data were collected through a specially designed self-administered questionnaire. Results: In total, 280 (70%) medical students and 120 (30%) nursing students were included in the study. The reported prevalence of plagiarism was 54.3%, with a slightly higher prevalence among male students compared to female students (54.9% versus 53.8%; P = 0.820) and medical students compared to nursing students (58.9% versus 43.3%; (P = 0.004). Alarmingly, 34.8% of the students did not know what plagiarism was, and only 28% were aware of the legal consequences of plagiarism. Reported reasons for plagiarising included laziness and the ease with which others’ work could be plagiarised, confusion, cultural reasons and pressure to meet deadlines. Conclusion: There was a lack of understanding of plagiarism and its legal ramifications among undergraduate medical and nursing students in Erbil. The findings of this study indicate that there is an urgent need to increase students’ understanding of plagiarism and its consequences so as to reduce the incidence of this type of academic misconduct.

Background Familiarity with a simulation platform can seduce modellers into accepting untested assumptions for convenience of implementation. These assumptions may have consequences greater than commonly suspected, and it is important that modellers remain mindful of assumptions and remain diligent with sensitivity testing. Methods Familiarity with a technique can lead to complacency, and alternative approaches and software can reveal untested assumptions. Visual modelling environments based on system dynamics may help to make critical assumptions more evident by offering an accessible visual overview and empowering a focus on representational rather than computational efficiency. This capacity is illustrated using a cohort-based forest growth model developed for mixed species forest. Results The alternative model implementation revealed that untested assumptions in the original model could have substantial influence on simulated outcomes. Conclusions An important implication is that modellers should remain conscious of all assumptions, consider alternative implementations that reveal assumptions more clearly, and conduct sensitivity tests to inform decisions.

يتناول هذا البحث جريمة الغدر، وهي أحد أشكال إساءة استخدام الوظيفة العامة ذات الوصف الجنائي، وهي جريمة خطيرة تتعلق بنزاهة الوظيفة لما تشكله من غدر في المواطنين الكلفين بالأعباء المالية العامة، حيث تقوم على استغلال الجاني لوظيفته لتحقيق منفعة غير مشروعة، لذا كان هدف المشرع من إقرارها حماية الأفراد من أن يتحملوا أعباء مالية غير مستحقة أو ما يزيد عن المستحق، بالإضافة إلى حماية الثقة القائمة بين الأفراد والدولة، كما يسلط الضوء على أركان جريمة الغدر، حيث يتطلب لقيامها توفر ركنا مفترضا يتمثل في تحقق صفة خاصة في الجاني وصفة المال المستولي عليه موضوع الجريمة، وركنا ماديا يتمثل في السلوك الذي يأخذ إحدى صورتي الطلب أو الأخذ، ومحل الجريمة المنصب على أحد الأعباء المالية العامة، والجباية غير المشروعة للأموال، وركنا معنويا يتمثل في القصد العام الذي يقوم على توافر عنصري العلم والإرادة دون الحاجة إلى القصد الجنائي الخاص، وكذلك مراجعة الأحكام العقابية والإجرائية المحددة للجريمة.