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We study the clustering of galaxies detected at i < 22.5 in the Science Verification observations of the Dark Energy Survey (DES). Two-point correlation functions are measured using 2.3 × 106 galaxies over a contiguous 116 deg2 region in five bins of photometric redshift width Δz = 0.2 in the range 0.2 < z < 1.2. The impact of photometric redshift errors is assessed by comparing results using a template-based photo-z algorithm (BPZ) to a machine-learning algorithm (TPZ). A companion paper presents maps of several observational variables (e.g. seeing, sky brightness) which could modulate the galaxy density. Here we characterize and mitigate systematic errors on the measured clustering which arise from these observational variables, in addition to others such as Galactic dust and stellar contamination. After correcting for systematic effects, we measure galaxy bias over a broad range of linear scales relative to mass clustering predicted from the Planck Λ cold dark matter model, finding agreement with the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) measurements with X2 of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. We test a 'linear bias' model, in which the galaxy clustering is a fixed multiple of the predicted non-linear dark matter clustering. The precision of the data allows us to determine that the linear bias model describes the observed galaxy clustering to 2.5 per cent accuracy down to scales at least 4-10 times smaller than those on which linear theory is expected to be sufficient. [ABSTRACT FROM AUTHOR]

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Copyright of BJS Open is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of BJS Open is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of BJS Open is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents information about the thirty-fourth Annual Conference of American Association for Public Opinion Research, held at The Inn at Buck Hill Falls, Pennsylvania, between May 31 and June 3, 1979. For the second time, the conference had two plenary sessions. In the first, Harry O'Neill, Donald Hughes, and Mervin Field led a lively exchange on polling, political advocacy, and the public interest. The second, on polls in the legal and regulatory process, featured Wallace Snyder from the Federal Trade Commission and Hans Zeisel. Both sessions had high attendance and robust participation by members of the audience. This year the conference presented several exhibits, including a demonstration of random digit dialing, a display of U. S. Census forms and publications, and an NORC exhibit of questionnaires used since 1941, which Offered both historical data and a bit, of opinion polling nostalgia. The conference program covered 20 regular sessions and 15 roundtable sessions, with attendance generally strong at all of them.

The issue of dynamic efficiency is central to analyses of capital accumulation and economic growth. Yet the question of what characteristics should examined to determine whether actual economics are dynamically efficient is unresolved. This paper develops a criterion for determining whether an economy is dynamically efficient. The criterion, which holds for economies in which technological progress and population growth are stochastic, involves a comparison of the cash flows generated by capital with the level of investment. Its application to the United States economy and the economies of other major OECD nations suggests that they are dynamically efficient. [ABSTRACT FROM AUTHOR]