2,547 research outputs found
Social Class and the Fertility Transition: A Critical Comment on the Statistical Results Reported in Simon Szreter's Fertility, Class and Gender in Britain, 1860-1940
Simon Szreter’s book Fertility, Class, and Gender in Britain, 1860-1940 argues that social and economic class fails to explain the cross-sectional differences in marital fertility as reported in the 1911 census of England and Wales. Szreter’s conclusion made the book immediately influential, and it remains so. This finding matters a great deal for debates about the causes of the European fertility decline of the nineteenth and twentieth centuries. For decades scholars have argued whether the main forces at work were ideational or social and economic. This note reports a simple re-analysis of Szreter’s own data, which suggests that social class does explain cross-sectional differences in English marital fertility in 1911.fertility transition, 1911 Census of England and Wales
Driven to Distraction: Self-Supervised Distractor Learning for Robust Monocular Visual Odometry in Urban Environments
We present a self-supervised approach to ignoring "distractors" in camera
images for the purposes of robustly estimating vehicle motion in cluttered
urban environments. We leverage offline multi-session mapping approaches to
automatically generate a per-pixel ephemerality mask and depth map for each
input image, which we use to train a deep convolutional network. At run-time we
use the predicted ephemerality and depth as an input to a monocular visual
odometry (VO) pipeline, using either sparse features or dense photometric
matching. Our approach yields metric-scale VO using only a single camera and
can recover the correct egomotion even when 90% of the image is obscured by
dynamic, independently moving objects. We evaluate our robust VO methods on
more than 400km of driving from the Oxford RobotCar Dataset and demonstrate
reduced odometry drift and significantly improved egomotion estimation in the
presence of large moving vehicles in urban traffic.Comment: International Conference on Robotics and Automation (ICRA), 2018.
Video summary: http://youtu.be/ebIrBn_nc-
What you don’t know can kill you
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141180/1/rth212056.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141180/2/rth212056_am.pd
Intensive community supervision for high-risk offenders does little to reduce crime
America’s prisons are becoming increasingly overcrowded, with many authorities seeking to shift the supervision of offenders into the community as a result. In new research, Jordan M. Hyatt & Geoffrey C. Barnes investigate the use of intensive supervision for the most serious offenders. In a study of more than 800 high risk probationers, they find that those who were closely supervised were just as likely to reoffend as those who were not, and in a similar time frame. They also find that closer supervision is linked with higher rates of absconding, incarceration and probation violations
Social Class and the Fertility Transition: A Critical Comment on the Statistical Results Reported in Simon Szreter’s Fertility, Class and Gender in Britain, 1860-1940
Algorithmic risk assessment policing models: Lessons from the Durham Constabulary HART model
To permit the use of unproven algorithms in the police service in a controlled and time-limited way, and as part of a combination of approaches to combat algorithmic opacity, our research proposes ‘ALGO-CARE’, a guidance framework of some of the key legal and practical concerns that should be considered in relation to the use of algorithmic risk assessment tools by the police. As is common across the public sector, the UK police service is under pressure to do more with less, and to target resources more efficiently and take steps to identify threats proactively; for example under risk-assessment schemes such as ‘Clare’s Law’ and ‘Sarah’s Law’. Algorithmic tools promise to improve a police force’s decision-making and prediction abilities by making better use of data (including intelligence), both from inside and outside the force. This research uses Durham Constabulary’s Harm Assessment Risk Tool (HART) as a case-study. HART is one of the first algorithmic models to be deployed by a UK police force in an operational capacity. Our research comments upon the potential benefits of such tools, explains the concept and method of HART and considers the results of the first validation of the model’s use and accuracy. The research concludes that for the use of algorithmic tools in a policing context to result in a ‘better’ outcome, that is to say, a more efficient use of police resources in a landscape of more consistent, evidence-based decision-making, then an ‘experimental’ proportionality approach should be developed to ensure that new solutions from ‘big data’ can be found for criminal justice problems traditionally arising from clouded, non-augmented decision-making. Finally, our research notes that there is a sub-set of decisions around which there is too great an impact upon society and upon the welfare of individuals for them to be influenced by an emerging technology; to an extent, in fact, that they should be removed from the influence of algorithmic decision-making altogether
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Implementing a Burglary Prevention Program with Evidence-Based Tracking: A Case Study
This case study reports an effort to measure the implementation of all elements of a burglary intervention known as 'super cocooning', in a part of the City of Manchester Division of the Greater Manchester Police (Gorton North and South) identified as an area of high repeat and near repeat burglary.College of Policing and Greater Manchester Polic
Noise suppression using symmetric exchange gates in spin qubits
We demonstrate a substantial improvement in the spin-exchange gate using
symmetric control instead of conventional detuning in GaAs spin qubits, up to a
factor-of-six increase in the quality factor of the gate. For symmetric
operation, nanosecond voltage pulses are applied to the barrier that controls
the interdot potential between quantum dots, modulating the exchange
interaction while maintaining symmetry between the dots. Excellent agreement is
found with a model that separately includes electrical and nuclear noise
sources for both detuning and symmetric gating schemes. Unlike exchange control
via detuning, the decoherence of symmetric exchange rotations is dominated by
rotation-axis fluctuations due to nuclear field noise rather than direct
exchange noise.Comment: 5 pages main text (4 figures) plus 5 pages supplemental information
(3 figures
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