More information, better jobs? : occupational stratification and labor market segmentation in the United States' information labor force

This article examines the mix of good and bad jobs in the restructuring of United States' labor markets for information work between 1900 and 1980. ls the information sector still growing relative to other occupational sectors? What is the relative proportion of good to bad jobs in the information sector today? ls the mix of good bad jobs within the information sector changing over time? To answer these questions, we examine changes in the relative size of the information sector's labor markers and changes in five occupational strata within it - professional, semiprofessional, supervisory and upper-level sales personnel, clerks, and blue-collar workers.The information occupations mushroomed in size from 17% of the United States workforce in 1900 to over 50% in 1980. Information sector jobs vary widely in quality. Few information sector jobs are fully professional, and clerical jobs form the largest single occupational stratum. When we examined the growth of the various strata between 1900 and 1980, we found that clerical jobs became more dominant, not less dominant. But this distribution has been masked by the steady growth of information sector jobs in the highly professional and semiprofessional strata, as well as clerical jobs. The occupational stratum between clerks and semiprofessionals - the supervisory and upper-level sales workers - has steadily declined in relative size.Two lower strata - clerks and sales and supervisory workers - account for 55% of the jobs in the information sector. Our data suggest that information labor markets are divided into relatively impermeable segments. As the information sector expanded, it took on many characteristics of the overall economy. It includes a mix of jobs that are diverse in their pay, status, and power. Its internal divisions reflect patterns of segmentation that have developed elsewhere in the society - a dual labor market. Overall, the information sector has become sufficiently large that it is not an alternative to the dominant social order - it simply reproduces many of its features

Transparency in International Investment Law: The Good, the Bad, and the Murky

How transparent is the international investment law regime, and how transparent should it be? Most studies approach these questions from one of two competing premises. One camp maintains that the existing regime is opaque and should be made completely transparent; the other finds the regime sufficiently transparent and worries that any further transparency reforms would undermine the regime’s essential functioning. This paper explores the tenability of these two positions by plumbing the precise contours of transparency as an overarching norm within international investment law. After defining transparency in a manner befitting the decentralized nature of the regime, the paper identifies international investment law’s key transparent, semi-transparent, and non-transparent features. It underscores that these categories do not necessarily map onto prevailing normative judgments concerning what might constitute good, bad, and murky transparency practices. The paper then moves beyond previous analyses by suggesting five strategic considerations that should factor into future assessments of whether and how particular aspects of the regime should be rendered more transparent. It concludes with a tentative assessment of the penetration, recent evolution, and likely trajectory of transparency principles within the contemporary international investment law regime

Privacy as a Public Good

Privacy is commonly studied as a private good: my personal data is mine to protect and control, and yours is yours. This conception of privacy misses an important component of the policy problem. An individual who is careless with data exposes not only extensive information about herself, but about others as well. The negative externalities imposed on nonconsenting outsiders by such carelessness can be productively studied in terms of welfare economics. If all relevant individuals maximize private benefit, and expect all other relevant individuals to do the same, neoclassical economic theory predicts that society will achieve a suboptimal level of privacy. This prediction holds even if all individuals cherish privacy with the same intensity. As the theoretical literature would have it, the struggle for privacy is destined to become a tragedy. But according to the experimental public-goods literature, there is hope. Like in real life, people in experiments cooperate in groups at rates well above those predicted by neoclassical theory. Groups can be aided in their struggle to produce public goods by institutions, such as communication, framing, or sanction. With these institutions, communities can manage public goods without heavy-handed government intervention. Legal scholarship has not fully engaged this problem in these terms. In this Article, we explain why privacy has aspects of a public good, and we draw lessons from both the theoretical and the empirical literature on public goods to inform the policy discourse on privacy

Revolutionaries and spies: Spy-good and spy-bad graphs

We study a game on a graph $G$ played by $r$ {\it revolutionaries} and $s$ {\it spies}. Initially, revolutionaries and then spies occupy vertices. In each subsequent round, each revolutionary may move to a neighboring vertex or not move, and then each spy has the same option. The revolutionaries win if $m$ of them meet at some vertex having no spy (at the end of a round); the spies win if they can avoid this forever. Let $\sigma(G,m,r)$ denote the minimum number of spies needed to win. To avoid degenerate cases, assume |V(G)|\ge r-m+1\ge\floor{r/m}\ge 1. The easy bounds are then \floor{r/m}\le \sigma(G,m,r)\le r-m+1. We prove that the lower bound is sharp when $G$ has a rooted spanning tree $T$ such that every edge of $G$ not in $T$ joins two vertices having the same parent in $T$. As a consequence, \sigma(G,m,r)\le\gamma(G)\floor{r/m}, where $\gamma(G)$ is the domination number; this bound is nearly sharp when $\gamma(G)\le m$. For the random graph with constant edge-probability $p$, we obtain constants $c$ and $c'$ (depending on $m$ and $p$) such that $\sigma(G,m,r)$ is near the trivial upper bound when $r<c\ln n$ and at most $c'$ times the trivial lower bound when $r>c'\ln n$. For the hypercube $Q_d$ with $d\ge r$, we have $\sigma(G,m,r)=r-m+1$ when $m=2$, and for $m\ge 3$ at least $r-39m$ spies are needed. For complete $k$-partite graphs with partite sets of size at least $2r$, the leading term in $\sigma(G,m,r)$ is approximately $\frac{k}{k-1}\frac{r}{m}$ when $k\ge m$. For $k=2$, we have \sigma(G,2,r)=\bigl\lceil{\frac{\floor{7r/2}-3}5}\bigr\rceil and \sigma(G,3,r)=\floor{r/2}, and in general $\frac{3r}{2m}-3\le \sigma(G,m,r)\le\frac{(1+1/\sqrt3)r}{m}$.Comment: 34 pages, 2 figures. The most important changes in this revision are improvements of the results on hypercubes and random graphs. The proof of the previous hypercube result has been deleted, but the statement remains because it is stronger for m<52. In the random graph section we added a spy-strategy resul