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© GESIS. This article examines the stratifying effects of economic classifications. We argue that in the neoliberal era market institutions increasingly use actuarial techniques to split and sort individuals into classification situations that shape life-chances. While this is a general and increasingly pervasive process, our main empirical illustration comes from the transformation of the credit market in the United States. This market works as both as a leveling force and as a condenser of new forms of social difference. The U.S. banking and credit system has greatly broadened its scope over the past twenty years to incorporate previously excluded groups. We observe this leveling tendency in the expansion of credit amongst lower-income households, the systematization of overdraft protections, and the unexpected and rapid growth of the fringe banking sector. But while access to credit has democratized, it has also differentiated. Scoring technologies classify and price people according to credit risk. This has allowed multiple new distinctions to be made amongst the creditworthy, as scores get attached to different interest rates and loan structures. Scores have also expanded into markets beyond consumer credit, such as insurance, real estate, employment, and elsewhere. The result is a cumulative pattern of advantage and disadvantage with both objectively measured and subjectively experienced aspects. We argue these private classificatory tools are increasingly central to the generation of "market-situations", and thus an important and overlooked force that structures individual life-chances. In short, classification situations may have become the engine of modern class situations.

This article examines the stratifying effects of economic classifications. We argue that in the neoliberal era market institutions increasingly use actuarial techniques to split and sort individuals into classification situations that shape life-chances. While this is a general and increasingly pervasive process, our main empirical illustration comes from the transformation of the credit market in the United States. This market works as both as a leveling force and as a condenser of new forms of social difference. The U.S. banking and credit system has greatly broadened its scope over the past twenty years to incorporate previously excluded groups. We observe this leveling tendency in the expansion of credit amongst lower-income households, the systematization of overdraft protections, and the unexpected and rapid growth of the fringe banking sector. But while access to credit has democratized, it has also differentiated. Scoring technologies classify and price people according to credit risk. This has allowed multiple new distinctions to be made amongst the creditworthy, as scores get attached to different interest rates and loan structures. Scores have also expanded into markets beyond consumer credit, such as insurance, real estate, employment, and elsewhere. The result is a cumulative pattern of advantage and disadvantage with both objectively measured and subjectively experienced aspects. We argue these private classificatory tools are increasingly central to the generation of "market-situations", and thus an important and overlooked force that structures individual life-chances. In short, classification situations may have become the engine of modern class situations.

What do markets see when they look at people? Information dragnets increasingly yield huge quantities of individual-level data, which are analyzed to sort and slot people into categories oftaste, riskiness or worth. These tools deepen the reach of the market and define new strategies of profit-making. We present a new theoretical framework for understanding their development. We argue that (a) modern organizations follow an institutional data imperative to collect as much data as possible, (b) as a result of the analysis and use of this data, individuals accrue a form of capital flowing from their positions as measured by various digital scoring and ranking methods; and (c) the facticity of these scoring methods makes them organizational devices with potentially stratifying effects. They offer firms new opportunities to structure and price offerings to consumers. For individuals, they create classification situations that identify shared life-chances in product and service markets. We discuss the implications of these processes and argue that they tend toward a new economy of moral judgment, where outcomes are experienced as morally deserved positions based on prior good actions and good tastes, as measured and classified by this new infrastructure of data collection and analysis.

This article examines the stratifying effects of economic classifications. We argue that in the neoliberal era market institutions increasingly use actuarial techniques to split and sort individuals into classification situations that shape life-chances. While this is a general and increasingly pervasive process, our main empirical illustration comes from the transformation of the credit market in the United States. This market works as both as a leveling force and as a condenser of new forms of social difference. The U.S. banking and credit system has greatly broadened its scope over the past twenty years to incorporate previously excluded groups. We observe this leveling tendency in the expansion of credit amongst lower-income households, the systematization of overdraft protections, and the unexpected and rapid growth of the fringe banking sector. But while access to credit has democratized, it has also differentiated. Scoring technologies classify and price people according to credit risk. This has allowed multiple new distinctions to be made amongst the creditworthy, as scores get attached to different interest rates and loan structures. Scores have also expanded into markets beyond consumer credit, such as insurance, real estate, employment, and elsewhere. The result is a cumulative pattern of advantage and disadvantage with both objectively measured and subjectively experienced aspects. We argue these private classificatory tools are increasingly central to the generation of "market-situations", and thus an important and overlooked force that structures individual life-chances. In short, classification situations may have become the engine of modern class situations. © 2013 .

Australia exports a major proportion of its agricultural production and is highly dependent on maintaining and developing access to, and competitiveness in, export markets. To preserve Australia's status as a provider of high quality grain, the majority of Australian primary producers rely on pesticides to protect their crops from pests and diseases, particularly in post-harvest situations. The Australian Pesticides and Veterinary Medicines Authority (APVMA) supports Australian agriculture by registering and allowing the supply of safe and effective animal health and crop protection products. A residue risk management continuum is established when the effectiveness of chemical registration and control of chemical use regulations is assessed through residue monitoring programs. Programs assess good agricultural practice and provide traceback capacity to investigate areas of concern. Risk communication provides opportunities for continuous improvement. In the early 1960s, the Australian Government established a non-regulatory body, the national residue survey (NRS). In 2008-2009, random monitoring programs were conducted for over 50 commodities (21 grains, five horticultural commodities, 11 fish species, 12 animal species, honey and egg with over 20,000 samples collected for analytical testing. The NRS grain residue monitoring program is presented as a case study of the residue risk management continuum demonstrating to overseas markets the high level of residue integrity of Australian grain. Over 4,000 grain samples are collected and analysed per annum. Most of the samples are collected in the bulk export program where samples are collected from every hatch of every ship loaded at the seventeen Australian grain export terminals. The chemical screens have expanded beyond the multi-residue screen (MRS) insecticides, fungicides and herbicides, to include phosphine, additional herbicides (not included in the MRS), heavy metals and mycotoxins. In its current form, the NRS grains program provides 15 years of residue testing data which demonstrates a very high degree of conformance with Australian MRLs and the import tolerances of overseas trading partners. In addition, trends in residue testing data demonstrate a decline in the frequency of residue detections and the levels of residue detected. To be confident that residue testing results meet the requisite standards, the reliability of the Australian analyses must be assured. The NRS laboratory performance evaluation system has been developed to provide that assurance, using a range of proficiency tests and other techniques in the selection of laboratories for NRS work. Residue testing results are reported against both Australian MRLs and the international MRLs which apply in the relevant export market. NRS maintains databases of overseas MRLs and compares its residue testing results of exported commodities against those standards. Grain marketers receive certificates of analysis, in the form of NRS residue testing results, for each shipment prior to arrival at the overseas market.Keywords: Grain, Pesticide, residue, monitoring program, residue risk management