Creative accounting in the British Industrial Revolution: Cotton manufacturers and the ‘Ten Hours’ Movement.

The paper examines an early case of creative accounting, and how, during British industrialization, accounting was enlisted by the manufacturers’ interest to resist demands, led by the ‘Ten hours’ movement, for limiting the working day. In contrast to much of the prior literature, which argues that entrepreneurs made poor use of accounting techniques in the British industrial revolution, the paper shows that there was considerable sophistication in their application to specific purposes, including political lobbying and accounting for the accumulation of capital. To illustrate lobbying behaviour, the paper examines entrepreneurs’ use of accounting to resist the threat of regulation of working time in textile mills. It explains why accounting information became so important in the debate over factory legislation. In doing so, it shows that a significant element was the accounting evidence of one manufacturer in particular, Robert Hyde Greg, which had a strong impact on the outcome of the parliamentary process. The paper uses archival evidence to illustrate how accounting was used in Greg’s enterprise and the reality of its economic performance. The archival evidence of actual performance is then contrasted with the figures presented by Greg to the Factories Inquiry Commission, convened by the House of Commons in 1833-1834 to hear witnesses from the manufacturing interest. These sets of figures are compared and contrasted and discrepancies noted. Conclusions show that the discrepancies were substantial, motivated by Greg’s incentives to present a particular view of low profits, high fixed costs, and the threat of cheaper overseas competition. The figures appeared to lend some credibility to the apparent plight of manufacturers and to Nassau Senior’s flawed argument about all profit being earned in the ‘last hour’ of the working day. The consequence was a setback for the Ten Hours movement, leading to a further intensification of political struggles over working conditions in the 1840s

Creative accounting in the British Industrial Revolution: Cotton manufacturers and the ‘Ten Hours’ Movement.

The paper examines an early case of creative accounting, and how, during British industrialization, accounting was enlisted by the manufacturers’ interest to resist demands, led by the ‘Ten hours’ movement, for limiting the working day. In contrast to much of the prior literature, which argues that entrepreneurs made poor use of accounting techniques in the British industrial revolution, the paper shows that there was considerable sophistication in their application to specific purposes, including political lobbying and accounting for the accumulation of capital. To illustrate lobbying behaviour, the paper examines entrepreneurs’ use of accounting to resist the threat of regulation of working time in textile mills. It explains why accounting information became so important in the debate over factory legislation. In doing so, it shows that a significant element was the accounting evidence of one manufacturer in particular, Robert Hyde Greg, which had a strong impact on the outcome of the parliamentary process. The paper uses archival evidence to illustrate how accounting was used in Greg’s enterprise and the reality of its economic performance. The archival evidence of actual performance is then contrasted with the figures presented by Greg to the Factories Inquiry Commission, convened by the House of Commons in 1833-1834 to hear witnesses from the manufacturing interest. These sets of figures are compared and contrasted and discrepancies noted. Conclusions show that the discrepancies were substantial, motivated by Greg’s incentives to present a particular view of low profits, high fixed costs, and the threat of cheaper overseas competition. The figures appeared to lend some credibility to the apparent plight of manufacturers and to Nassau Senior’s flawed argument about all profit being earned in the ‘last hour’ of the working day. The consequence was a setback for the Ten Hours movement, leading to a further intensification of political struggles over working conditions in the 1840s

Ethical considerations in the use of Machine Learning for research and statistics.

This paper, based upon new guidance created in collaboration with researchers from several national statistical institutes, explores the main ethical considerations associated with the use of machine learning techniques for aggregate statistics. The aim of this paper is to provide applied, practical ethical guidance for researchers using machine learning techniques. Following an extensive literature review, alongside discussion and collaboration with a number of national statistical institutes, it was identified that there was a need for applied guidance on the use of machine learning for the production of official statistics by the international research and statistical community. Feedback was gathered from interested stakeholders, which found that whilst there were resources available to researchers relating to the ethical considerations of machine learning projects, these focus mainly on operational uses of machine learning, and furthermore, lacked advice on how to practically mitigate ethical issues that arise throughout the project lifecycle. The guidance focuses on four main ethical considerations, found to be prevalent within machine learning research, and offers ways to mitigate these issues should they arise. These are: the importance of minimising and mitigating social bias and discrimination within machine learning research, and clearly communicating these, and the limitations of our research; the need to consider the transparency and explainability of machine learning research, and the implications this has for reproducibility; the importance of maintaining accountability throughout machine learning processes, ensuring that models are used only for their intended purposes, and that different stakeholders are aware of their responsibilities; the need to consider the confidentiality and privacy risks arising from the data used, both in relation to training data which is fed into the machine, and outputs resulting from the machine learning’s findings. The guidance has been well-received following its release, and feedback from the wider user community to date has been positive. The IPDLN conference provides an opportunity for further feedback to be collated to ensure that the guidance continues to be valuable to its intended audience

Analysis of mycobiomes to uncover biodiversity: a case study between soil fungi and orchid species in Sweden

Abstracts from the April 12-14, 2019 MASC Conferenc

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the top quark mass using charged particles in pp collisions at root s=8 TeV

Peer reviewe

Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

Peer reviewe