Why using technology to spy on home-working employees may be a bad idea

People feel that intrusive control harms their dignity, and lose intrinsic motivation to perform well, write Gabriel Burdin, Simon D. Halliday, and Fabio Landin

Advanced Technologies and Worker Voice

The interplay between labour institutions and firm-level adoption of new technologies such as robotics andother advanced digital tools remains poorly understood. Using a cross-sectional sample of more than 20,000European establishments, we document a positive association between shop-floor employee representation (ER)and utilization of emerging technologies. We explore mechanisms driving this correlation by exploiting richinformation on the role played by ER in relation to well-defined decision areas of management, such as workorganization, dismissals, training and working time. In addition, we conduct a quantitative case study usinga panel of Italian firms and exploiting size-contingent policy rules governing the operation of ER bodies inthe context of a local-randomization regression discontinuity design. The analysis suggests a positive effectof ER on investments in advanced technologies around the firm size cut-off, although results are sensitiveto type of technology and specification choices. We also document positive effects on training and processinnovation, and no evidence of changes in composition of employment. Our findings cast doubt on the ideathat ER discourages technology adoption. Rather, ER seems to influence workplace practices that enhance thecomplementarity between labour and new advanced technologies

The Economic Advantage of Preventative Health Care in Prisons

The Economic Advantage of Preventative Health Care in Prison

Contested Transparency: Digital Monitoring Technologies and Worker Voice

Advances in artificial intelligence and data analytics have notably expanded employers’ monitoring and surveillance capabilities, facilitating the accurate observability of work effort. There is an ongoing debate among academics and policymakers about the productivity and broader welfare implications of digital monitoring (DM) technologies. In this context, many countries confer information, consultation and codetermination rights to employee representation (ER) bodies on matters related to the workplace governance of these technologies. Using a cross-sectional sample of more than 21000 European establishments, we document a positive association between ER and the utilization of DM technologies. We also find a positive effect of ER on DM utilization in the context of a localrandomization regression discontinuity analysis that exploits size-contingent policy rules governing the operation of ER bodies in Europe. Finally, in an exploratory analysis, we find a positive association between DM and process innovations, particularly in establishments where ER bodies are present and a large fraction of workers perform jobs that require finding solutions to unfamiliar problems. We interpret these findings through the lens of a labor discipline model in which the presence of ER bodies affect employer’s decision to invest in DM technologies

Epithelial segmentation from in situ hybridisation histological samples using a deep central attention learning approach

The assessment of pathological samples by molecular techniques, such as in situ hybridization (ISH) and immunohistochemistry (IHC), has revolutionised modern Histopathology. Most often it is important to detect ISH/IHC reaction products in certain cells or tissue types. For instance, detection of human papilloma virus (HPV) in oropharyngeal cancer samples by ISH products is difficult and remains a tedious and time consuming task for experts. Here we introduce a proposed framework to segment epithelial regions in oropharyngeal tissue images with ISH staining. First, we use colour deconvolution to obtain a counterstain channel and generate input patches based on superpixels and their neighbouring areas. Then, a novel deep attention residual network is applied to identify the epithelial regions to produce an epithelium segmentation mask. In the experimental results, comparing the proposed network with other state-of-the-art deep learning approaches, our network provides a better performance than region-based and pixel-based segmentations

The perception of facial asymmetry using 3-dimensional simulated images

Objective: To investigate the perception of facial asymmetry in young adults to identify the amounts of chin asymmetry that can be regarded as normal and may benefit from correction. Materials and Methods: Three-dimensional (3D) images of 56 individuals of mixed ethnicity were obtained and used to produce average 3D images of male and female faces. Distortion was then applied to these average faces using a 3D graphics package to simulate different amounts of chin point asymmetry. Five observer groups (lay individuals, dental students, dental care professionals, dental practitioners, and orthodontists) assessed timed presentations of 3D images, rating them as “normal,” “acceptable,” or “would benefit from correction.” Time-to-event analysis was used to assess the level of chin asymmetry perceived as normal and beneficial for correction for each group. Results: The factors influencing the perception of facial asymmetry were the degree of asymmetry and the observer group. Direction of the asymmetry and gender of the assessed individual did not affect the perception of asymmetry, except in the 4- to 6-mm distortion range. The gender of the observer had no influence on perception. There were statistically significant differences in the amounts of asymmetry that the laypeople and orthodontists considered to be normal (5.6 ± 2.7 mm and 3.6 ± 1.5 mm, respectively; P < .001) and felt would benefit from surgical correction (11.8 ± 4.0 mm and 9.7 ± 3.0 mm, respectively; P  =  .001). Conclusions: Perception of asymmetry is affected by the amount of asymmetry and the observer group, with orthodontists being more critical

Three Dimensional Visualization and Fractal Analysis of Mosaic Patches in Rat Chimeras: Cell Assortment in Liver, Adrenal Cortex and Cornea

The production of organ parenchyma in a rapid and reproducible manner is critical to normal development. In chimeras produced by the combination of genetically distinguishable tissues, mosaic patterns of cells derived from the combined genotypes can be visualized. These patterns comprise patches of contiguously similar genotypes and are different in different organs but similar in a given organ from individual to individual. Thus, the processes that produce the patterns are regulated and conserved. We have previously established that mosaic patches in multiple tissues are fractal, consistent with an iterative, recursive growth model with simple stereotypical division rules. Fractal dimensions of various tissues are consistent with algorithmic models in which changing a single variable (e.g. daughter cell placement after division) switches the mosaic pattern from islands to stripes of cells. Here we show that the spiral pattern previously observed in mouse cornea can also be visualized in rat chimeras. While it is generally held that the pattern is induced by stem cell division dynamics, there is an unexplained discrepancy in the speed of cellular migration and the emergence of the pattern. We demonstrate in chimeric rat corneas both island and striped patterns exist depending on the age of the animal. The patches that comprise the pattern are fractal, and the fractal dimension changes with the age of the animal and indicates the constraint in patch complexity as the spiral pattern emerges. The spiral patterns are consistent with a loxodrome. Such data are likely to be relevant to growth and cell division in organ systems and will help in understanding how organ parenchyma are generated and maintained from multipotent stem cell populations located in specific topographical locations within the organ. Ultimately, understanding algorithmic growth is likely to be essential in achieving organ regeneration in vivo or in vitro from stem cell populations.</p