Biased Assumptions Research Articles

Halo-based reconstruction of the cosmic mass density field

We present the implementation of a halo based method for the reconstruction of the cosmic mass density field. The method employs the mass density distribution of dark matter haloes and its environments computed from cosmological N-body simulations and convolves it with a halo catalog to reconstruct the dark matter density field determined by the distribution of haloes. We applied the method to the group catalog of Yang etal (2007) built from the SDSS Data Release 4. As result we obtain reconstructions of the cosmic mass density field that are independent on any explicit assumption of bias. We describe in detail the implementation of the method, present a detailed characterization of the reconstructed density field (mean mass density distribution, correlation function and counts in cells) and the results of the classification of large scale environments (filaments, voids, peaks and sheets) in our reconstruction. Applications of the method include morphological studies of the galaxy population on large scales and the realization of constrained simulations.

Claiming blame and giving credit? Unintended effects of how government and opposition frame the Europeanization of welfare

A framing experiment on the Europeanization of health care supports two assumptions derived from the ‘blame avoidance’ literature. The constrained perceptions assumption states that performance evaluations at different political levels have ‘zero-sum’ implications for each other. Empirically, those receiving positive integration frames become not only more positive about the European Union (EU) level, but also more negative about domestic performance (even though frames about such a performance were not provided). The opposite is found for negative frames. Further, the negative bias assumption implies that zero-sum adjustments are best triggered by negative blame frames rather than by positive ‘credit’ frames. Finally, in contrast to standard blame avoidance assumptions, the experiment mimics the realistic situation in which the opposition attacks integration and the government defends it. This reverses the prototypical blame avoidance situation and opens the way for unintended effects. Governments may paint EU-induced conditions in rosy colours, reflecting negatively on its domestic performance. Conversely, the opposition runs the risk of being too gloomy about integration for its own good, as negative EU welfare frames reflect positively on domestic performance.

Linguistic intergroup bias tells ingroup/outgroup orientation of bicultural Asian Americans

Traditional studies of ethnic relations focus on racialization between Whites and Blacks, or ethnic stratification between Whites and people of color. This study aims at broadening conventional studies of interethnic relations to examine racial attitudes among people who have internalized more than one culture – i.e., the biculturals and multiculturals. Social psychological research suggests that bicultural individuals are capable of switching between two cultural meaning frames depending on contextual demands. Bicultural individuals vary in how well they integrate the two cultural identities internalized in them – i.e., their bicultural identity integration levels (BII levels). Their BII levels lead to either culturally congruent or culturally incongruent behaviors among bicultural individuals. The underlying assumption of linguistic intergroup bias indicates that people tend to describe more abstractly observed positive ingroup behaviors and negative outgroup behaviors and describe more concretely observed negative ingroup behaviors and positive outgroup behaviors. In this study, bicultural Asian American participants are hypothesized to use language of either higher or lower abstraction to describe actions of positive and negative valence performed by either ethnic Asians or European Americans depending on the cultural priming they received and their BII levels. The demonstrated pattern of ingroup enhancement and outgroup derogation of the bicultural participants point out the perceived ingroup/outgroup orientation of these biculturals towards their coethnics and people of the mainstream culture. Effects of the cultural priming and impact of BII levels are also discussed.

Unbiased Stereological Techniques

This issue of NeuroQuantology is a special volume on the Unbiased Stereological Techniques. Articles in this issue are designed to give a basic and comprehensive view about the latest methods of design-based stereology. Stereology is a branch of morphometry, which provide simple methods to estimate various parameters by a correct sampling design, without making biased assumptions about the shape and size of the object or the frequency of the interested particles, or cells. The results of stereological estimations can be considered as unbiased, i.e. free from systematic error, from all practical angles. Papers included in the current issue give background information about some of the basic stereological methods, while the structure of papers are selected so that to put a view about the importance and practical implementation of some crucial points in the application general stereology. Papers are organized according to different subjects of modern stereological methods with a greater emphasis on neurostereology and we tried our best to make this issue as easy to read as possible. NeuroQuantology | March 2012 | Volume 10 | Issue 1 | Page 9-10

Bayesian multi-model projections of climate: generalization and application to ENSEMBLES results

In a previous study, we developed a Bayesian methodology for combining multi-model climate change simulations into a single probabilistic projection which addresses changes in inter- annual variability beyond changes in mean temperature, and which explicitly considers time-depen- dent model biases. We tested 2 different but equally plausible bias assumptions referred to as 'con- stant bias' and 'constant relationship'. The former assumes that the biases in control and scenario periods are approximately constant, following the implicit assumption in most climate change stud- ies. The latter approach follows seasonal forecasting procedures by assuming an approximate linear relationship between observed and simulated seasonal temperatures. In the present study we gener- alized this approach by combining the 2 bias assumptions into a single probabilistic projection. In cases where the 2 assumptions yield conflicting results, our methodology implicates a broader prob- ability density function, thereby reflecting the increased level of uncertainty. We applied the new method to area-mean seasonal temperature distributions from global/regional climate model simula- tions of the ENSEMBLES project. Results are presented for changes in mean and variability between control (1961-1990) and scenario (2021-2050) periods. In comparison to the multi-model mean, the generalized Bayes method projected a considerably weaker warming during summer and autumn in much of continental Europe, a stronger winter warming in Scandinavia, France, eastern and central Europe, and a weaker warming in both summer and winter in the Mediterranean. These differences can be traced back to the models' difficulties in representing the natural interannual variability in these regions.

SYSTEMATIC EFFECTS ON DETERMINATION OF THE GROWTH FACTOR FROM REDSHIFT-SPACE DISTORTIONS

The linear growth factor of density perturbations is believed to be a powerful observable of future redshift surveys to probe physical properties of dark energy and to distinguish among gravity theories. We investigate systematic effects on determination of the growth factor f from a measurement of redshift-space distortions. Using N-body simulations we identify dark matter halos over a broad mass range. We compute the power spectra and correlation functions for the halos and then examine how well the redshift distortion parameter beta=f/b can be reconstructed as a function of halo mass. We find that beta measured for a fixed halo mass is generally a function of scale even on large scales, in contrast with the common expectation that beta approaches a constant described by Kaiser's formula on such scales. The scale dependence depends on the halo mass, being stronger for smaller halos. It also cannot be easily explained with the well-known distribution function of the halo peculiar velocities. We demonstrate that the biasing for smaller halos has larger nonlinearity and stochasticity, thus the linear bias assumption becomes worse for smaller halos. Only for massive halos with b>1.5, beta approaches the linear theory prediction on scales of r or pi/k>30Mpc/h. Luminous red galaxies (LRG), targeted by the SDSS-III's BOSS survey, tend to reside in very massive halos. Our results indicate that if the LRG is used for the measurement of redshift distortions, f can be measured unbiasedly. On the other hand, if one considers to use emission line galaxies, which are targeted by the BigBOSS survey and inhabited in halos of a broad mass range, the scale dependence of beta must be taken into account carefully; otherwise one might give incorrect constraints on dark energy or modified gravity theories. We also find that beta reconstructed in Fourier space behaves better than that in configuration space.

Claiming Blame and Giving Credit: Unintended Effects of how Government and Opposition Frame the Europeanization of Welfare

A framing experiment on the Europeanization of health care supports two assumptions derived from the “blame avoidance” literature. The constrained perceptions assumption states that performance evaluations at different political levels have “zero-sum” implications for each other. Empirically, those receiving positive integration frames not only become more positive about the EU level, but also more negative about domestic performance (even though frames about the such performance was not provided). The opposite is found for negative frames. Further, the negative bias assumption implies zero-sum adjustments are best triggered by negative blame frames than by positive “credit” frames. Finally, in contrast to standard blame avoidance assumptions the experiment mimics the realistic situation where the opposition attacks integrations and the government defends it. This reverses the prototypical blame avoidance situation and opens for unintended effects. Governments may paint EU-induced conditions in too rosy colours, reflecting negatively on domestic performance. Conversely, the opposition run the risk of being too gloomy about integration for its own good, as negative EU-welfare frames reflect positively on domestic performance.

Historical discharge measurements on the Middle Mississippi River, USA: no basis for ‘changing history’

AbstractThis study tests the hypothesis that historical float‐based discharge measurements on the Mississippi River systematically over‐stated actual flood flows by 10% to > 30% relative to measurements using current meters. This assertion has been repeated over the past 25 years and recently has been used to adjust historical discharges used for flood‐frequency analysis. This study tests the hypothesis above using 2150 historical discharge measurements digitized from the three principal gauging stations on the Middle Mississippi River (MMR): data that include 626 float‐based discharges and 1516 meter‐based discharges, including 122 paired measurements. Multiple comparative tests show that the hypothesis above cannot be supported; if anything, the float‐based measurements slightly underestimate flows (not over‐estimate) over a broad range of discharges up to large floods. In response to the purported data bias above (‘changing history’; Dieckmann RJ, Dyhouse GR. 1998. Changing history at St. Louis—adjusting historic flows for frequency analysis. First Federal Inter‐Agency Hydrologic Modeling Conference, April 20–22, 1998. Las Vegas, NV; 4·31–4·36), historical flood discharges on the MMR have been modified, most by 10–20% and several by > 30%. These altered discharges are now being promulgated, in particular, through the Upper Mississippi River System Flow Frequency Study (UMRSFFS). New flow frequencies, flood profiles, and new flood maps from the UMRSFFS may significantly underestimate the actual flood hazard on the MMR if the original hydrologic data have been erroneously altered on the basis of an assumption of data bias. Copyright © 2010 John Wiley & Sons, Ltd.

Real exchange rates, asset prices and terms of trade: A theoretical analysis

Abstract This paper develops a continuous-time two-country dynamic equilibrium model, in which the real exchange rates, asset prices, and terms of trade are jointly determined in the presence of nontradable goods. The model determines the relation between the financial markets and real goods markets in the world economy and their responses to various shocks under the home bias assumption. A positive domestic supply shock induces a positive return on the domestic asset markets and a deterioration of terms of trade that improves the foreign output and boosts the foreign asset markets. Demand shocks act in the opposite way. This model also analyses the impact of change in the relative price of nontradable to tradable goods on the terms of trade and asset markets. A higher productivity growth in tradable goods than in nontradable goods leads to a higher relative price of nontradable to tradable goods, which appreciates the real exchange rate, deteriorates the terms of trade, and depresses the domestic and foreign asset markets. A lower relative price of nontradable goods depreciates the real exchange rate, improves the terms of trade, and lifts both the domestic and foreign asset markets.

Quand le savant l’emporte sur le politique

In this article, I examine some of the reactions that William Julius Wilson’s The Declining Significance of Race has triggered among his colleagues and among black activists. I explain that some criticisms, clearly at odds with scientific research, are the result of ideological interpretations that completely divorce Wilson’s work from its scholarly context. Through my analysis of the controversy caused by Wilson thesis, I importantly address issues of methodology, analytical rigor, and objectivity in scholarly works and emphasize highly biased assumptions presented by myopic researchers who let racial and political ideology take precedence over objectivity.

Calculating Sample Size for Studies with Expected All‐or‐None Nonadherence and Selection Bias

We develop sample size formulas for studies aiming to test mean differences between a treatment and control group when all-or-none nonadherence (noncompliance) and selection bias are expected. Recent work by Fay, Halloran, and Follmann (2007, Biometrics 63, 465-474) addressed the increased variances within groups defined by treatment assignment when nonadherence occurs, compared to the scenario of full adherence, under the assumption of no selection bias. In this article, we extend the authors' approach to allow selection bias in the form of systematic differences in means and variances among latent adherence subgroups. We illustrate the approach by performing sample size calculations to plan clinical trials with and without pilot adherence data. Sample size formulas and tests for normally distributed outcomes are also developed in a Web Appendix that account for uncertainty of estimates from external or internal pilot data.

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions (“constant bias” and “constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961–1990) and scenario periods (2071–2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5–3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the “constant bias” and “constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this task.

Calibration of credibility of agnostic genome‐wide associations

Genome-wide testing platforms are increasingly used to promote "agnostic" approaches to the discovery of gene variants associated with the risk of many common diseases and quantitative traits. The early track record of genome-wide association (GWA) studies suggests that some proposed associations are replicated quite consistently with large-scale subsequent evidence from multiple studies, others have a more inconsistent replication record, some have failed to be replicated by independent investigators and many more early proposed associations await further replication. An important question is how to calibrate the credibility of these postulated associations. A simple Bayesian method is applied here to achieve such calibration. The variability of the estimated credibility is examined under different assumptions. Empirical examples are drawn from existing GWA studies. It is demonstrated that the credibility of different proposed associations can cover a very wide range. The credibility of specific associations usually remains relatively robust when different plausible assumptions are made (within a reasonable range) for the prior odds of an association being true, or the magnitude of the anticipated effect size for genetic associations. Heterogeneity and bias assumptions can have a more major impact on the credibility estimates and thus they need very careful consideration in each case. Credibility calibration may be used in conjunction with qualitative criteria for the appraisal of the cumulative evidence that take into consideration the amount, consistency, and protection from bias in the data.

A Phenomenological Analysis of Spiritual Seeking: Listening to Quester Voices

Prominent scholars have appealed for the use of diverse research methodologies to enhance ongoing work in the psychology of religion and spirituality. This article represents, to our knowledge, the first phenomenological investigation into quest religiosity. Results confirm earlier suggestions by Klaassen and McDonald (2001) that multiple, complex pathways or manifestations of quest are conceivable. Expressions of quest were identified by descriptions of spiritual and/or religious experience from questers who also retained varying degrees of faith commitments. Results suggest that several dimensions of quest religiosity have not been sufficiently understood, including its relational costs and a dialectic between making and abandoning commitments. We suggest that these results build on ideological surround analysis of religious orientation by confirming key elements of the quest model while identifying biased assumptions that limit the adequacy of current quest conceptualization. Further qualitative and longitudinal investigations are needed to understand the nuanced, socially embedded expressions of quest religiosity.

The 2dF-SDSS LRG and QSO Survey: the LRG 2-point correlation function and redshift-space distortions

We present a clustering analysis of luminous red galaxies (LRGs) using nearly 9000 objects from the final, three-year catalogue of the 2dF-SDSS LRG and QSO (2SLAQ) Survey. We measure the redshift-space two-point correlation function, ξ(s) and find that, at the mean LRG redshift of shows the characteristic downturn at small scales (1 h−1 Mpc) expected from line-of-sight velocity dispersion. We fit a double power law to ξ(s) and measure an amplitude and slope of s0 = 17.3+2.5−2.0 h−1 Mpc, γ = 1.03 ± 0.07 at small scales (s 4.5 h−1 Mpc). In the semiprojected correlation function, wp(σ), we find a simple power law with γ = 1.83 ± 0.05 and r0 = 7.30 ± 0.34 h−1 Mpc fits the data in the range 0.4 < σ < 50 h−1 Mpc, although there is evidence of a steeper power law at smaller scales. A single power law also fits the deprojected correlation function ξ(r), with a correlation length of r0 = 7.45 ± 0.35 h−1 Mpc and a power-law slope of γ = 1.72 ± 0.06 in the 0.4 < r < 50 h−1 Mpc range. But it is in the LRG angular correlation function that the strongest evidence for non-power-law features is found where a slope of γ = −2.17 ± 0.07 is seen at 1 < r < 10 h−1 Mpc with a flatter γ = −1.67 ± 0.07 slope apparent at r 1 h−1 Mpc scales. We use the simple power-law fit to the galaxy ξ(r), under the assumption of linear bias, to model the redshift-space distortions in the 2D redshift-space correlation function, ξ(σ, π). We fit for the LRG velocity dispersion, wz, the density parameter, Ωm and β(z), where β(z) = Ω0.6m/b and b is the linear bias parameter. We find values of wz = 330 km s−1, Ωm = 0.10+0.35−0.10 and β = 0.40 ± 0.05. The low values for wz and β reflect the high bias of the LRG sample. These high-redshift results, which incorporate the Alcock–Paczynski effect and the effects of dynamical infall, start to break the degeneracy between Ωm and β found in low-redshift galaxy surveys such as 2dFGRS. This degeneracy is further broken by introducing an additional external constraint, which is the value β(z = 0.1) = 0.45 from 2dFGRS, and then considering the evolution of clustering from z 0 to zLRG 0.55. With these combined methods we find Ωm(z = 0) = 0.30 ± 0.15 and β(z = 0.55) = 0.45 ± 0.05. Assuming these values, we find a value for b(z = 0.55) = 1.66 ± 0.35. We show that this is consistent with a simple ����high-peak’ bias prescription which assumes that LRGs have a constant comoving density and their clustering evolves purely under gravity.

Complementary and Alternative Treatments in Mental Health Care

Back to table of contents Previous article Next article Book ForumFull AccessComplementary and Alternative Treatments in Mental Health CareMARY ANNE BADARACCO M.D.,MARY ANNE BADARACCO M.D.Search for more papers by this author,Published Online:1 Aug 2007https://doi.org/10.1176/appi.ajp.2007.07061014AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail This is a clear, useful, timely, and often gracefully written book that delivers what it promises. It defines complementary and alternative treatments, places them in a historical context, provides a critical review of up-to-date and evidenced-based data on specific treatments relevant to adult mental health, summarizes each treatment’s known risks and benefits, and includes easily accessible tables, appendices, and other references. Written by 25 practicing psychiatrists, psychologists, and other health care professionals, it is offered as “a bridge between the orthodox theories and practices of conventional biomedicine and the established theories and practices of the world’s major systems of medicine as they pertain to mental health care” (p. xx).Part I, Background Issues, gives a nice overview of complementary and alternative treatments and has an especially useful chapter on legal, regulatory, and ethical issues surrounding its use. This chapter includes a model standard consent form grounded in good clinical sense and respect for patients, which is typical of the rest of the book. Another chapter refers to the definition of integrative approaches as those using “whole-person oriented healing and preventive methods” (p. 442). It distinguishes the goals of these approaches, achieving balance and enhanced self-awareness, from those of conventional medicine, which focuses on a return to good health.Part II reviews 13 specific treatments grouped into three categories: nonconventional biological treatments; lifestyle and women’s issues; and spirituality, mindfulness, and mind-body practices. Each separate chapter, written by one or more authors, employs a consistent format, with clear definitions, review of the evidence, safety considerations, and specific guidelines or recommendations. The authors clarify that the book is not designed as a manual for any specific treatment. Tables are used intelligently and well. Data are presented in an impartial manner, without any assumption of bias toward the specific treatment discussed. I found all of the chapters useful, but a few stand out. The one on omega-3 essential fatty acids is particularly balanced in its assessment of the often confusing and multiple claims of benefits for this treatment. Another on integrative medicine treatments for depression in women contains a solid and succinct review of the risks of conventional treatments of depression during pregnancy, with very practical suggestions about approaches that integrate complementary and alternative treatments. The chapter on religious beliefs and spirituality in mental health treatment is one of the best brief reviews I have ever read on the subject. It is pithy, straightforward, nonreductionistic, and nonpolemic. All chapters are written with regard to adult patients. There are no specific chapters on either the child/adolescent or geriatric populations. This is one of the few drawbacks of the book.The book closes with three helpful appendices: a table organized by major psychiatric disorder summarizing research findings of each complementary and alternative treatments approach described in the book, ranked according to levels of evidence supporting its use; a glossary of key complementary and alternative treatments terms; and a list of resources for complementary and alternative treatments.This is a very good book. One has the sense that real doctors are thinking about real patients in everyday situations. It is readable, interesting, serves as a fine reference book, and is available in paperback at a relatively modest cost. I would recommend it for medical students, trainees, practicing psychiatrists, and for our patients. By focusing on the evidence basis of these treatments and acknowledging the limitations of what we know, it could enhance discussions with our patients about their care. It might also serve as a basis for the incorporation of some elements of complementary and alternative treatments into various APA Practice Guidelines.Boston, Mass.This review (doi: 10.1176/appi.ajp.2007.07061014) was accepted for publication in May 2006. FiguresReferencesCited byDetailsCited ByNone Volume 164Issue 8 August, 2007Pages 1272-1272THE AMERICAN JOURNAL OF PSYCHIATRY August 2007 Volume 164 Number 8 Metrics PDF download History Published online 1 August 2007 Published in print 1 August 2007

What B Would Otherwise Do: A Critique of Conceptualizations of ‘Power’ in Organizational Theory

The paper presents a critique of organizational theories that is based upon Robert Dahl’s famous definition: ‘A has power over B to the extent that he can get B to do something that B would not otherwise do’. This definition highlights the fact that appreciating ‘power’ often demands knowledge not only about what B does but also about what B would otherwise do. Organizational theorists, it is argued, lacked such knowledge. Instead, they relied upon untested and ideologically biased assumptions concerning what B would otherwise do. Reviewing major conceptualizations of power in organizational theory, the paper unravels and categorizes six underlying assumptions of this sort. Then it goes on to promote an alternative, empirically-grounded and emically-oriented strategy for dealing with this issue. This strategy, it is argued, offers a new and less problematic research path with which to pursue the different theoretical interests in the field.

Case for Non-Biased Intelligence Testing Against Black Africans Has Not Been Made: A Comment on Rushton, Skuy, and Bons (2004)

This reply reviews the conceptual, methodological, and statistical foundations of Rushton, Skuy and Bons' article in this journal that compared Black Africans, Whites and East Indians on the Raven's Advanced Progressive Matrices, and concluded that the Raven's is an unbiased test. Through a technical re-analysis of both the internal and external validity criteria for test bias using data reported in the Rushton et al. paper, we demonstrate that the Raven's Matrices test is in fact biased against Black Africans. We take issue with several additional elements of Rushton et al.'s study, including the use of non-equivalent groups in test samples. We briefly review Rushton's racial-realist research agenda and show that the assumption of test bias is central to advancing that agenda. Industrial/organizational and occupational psychologists should critically analyze and re-evaluate the science employed in Rushton's racial-realist research and also should better understand the ethical and social implications of accepting his reports of research findings on test bias and White–Black IQ differences as established scientific facts.

Whitewashing Race: The Myth of a Color-Blind Society (review)

Reviewed by: Whitewashing Race: The Myth of a Color-Blind Society Julie Novkov Whitewashing Race: The Myth of a Color-Blind Society. By Michael K. Brown et al.Berkeley: University of California Press, 2003; pp xi + 338. $27.50. Whitewashing Raceis an extensive analysis of the current political and economic status of minorities in the United States, particularly African Americans, in the post–civil rights world of the twenty-first century. The book's agenda is driven home starkly throughout: the authors insist and empirically demonstrate that substantive equality remains out of reach for minorities across several dimensions of politics and society. The result is a thorough debunking of the recent wave of conservative attacks on the state's lukewarm efforts to intervene in and change the racial hierarchy embedded in the U.S. society and economy. The book is carefully researched and passionately argued, but I fear that it cannot achieve its primary goal of shifting the contemporary terms of debate about race. Perhaps, though, no single book could make that contribution. Scholars on the left might be able to work toward achieving a shift by starting with Whitewashing Race's ground-clearing efforts. The book does, as I will detail, accomplish much of the critical work it sets out to do. Whitewashing Racehas several different goals, all of which are urgent and commendable. First and foremost, the authors challenge the wave of conservative scholarship on race, picking apart the empirical claims of writers like Tamar Jacoby, Jim Sleeper, Dinesh D'Souza, Shelby Steele, and their favorite stalking horses Stephen and Abigail Thernstrom. Brown and his colleagues expose these writers' "racial realism" as a mask for racially biased assumptions and flawed research purporting to show that any lingering problems of minorities are solely of their own making. The second agenda is to shift the terms of the contemporary political debates about race, moving the focus away from individuals' behaviors and beliefs in favor of more focus on the institutionally embedded nature of racial hierarchy. Racism appears through this lens not as isolated behavior on the part of a few benighted individuals but instead as a multilayered system of promoting accumulation of resources (cultural, social, political, and economic) by whites at the expense of people of color. The third agenda, developed most directly in the book's final chapter, is to articulate a program for change that is sufficiently concrete and politically salient to gain support. To demolish the conservative argument against state intervention for civil and economic rights, the authors present a series of case studies. The greatest strength of the book is in this collaborative effort. The reader is taken on a multidisciplinary exploration of a single premise—that conservative thinking on race fails to recognize the continued complicity of institutions in creating and maintaining racial hierarchy—in the context of employment, [End Page 334]education, the criminal justice system, affirmative action and legal doctrine, and voting rights. The book could have been written as a series of discipline-based essays on each of these topics by the authors, all of whom are sharp, top scholars in their own right. Instead, the authors produced a unified argument, carefully nuanced and moderated by the disciplinary tensions and interdisciplinary collaborations among them. Here we have sociological and political work that carefully acknowledges and incorporates legal categories and legal work with deep and rigorous empirical roots. The economic analysis relies upon a thick conception of political institutions. The work on education relies upon political, sociological, and economic insights as well as recent legal theory. The final product coherently and systematically attacks the conservative case and dismantles it both theoretically and empirically. Though one can easily attribute primary authorship of the empirical chapters among the authors, one can just as easily see the deep collaboration among them and the greater strength that the arguments have for having gone through this refinement. The other great virtue of deep collaboration is that the book is quite readable. Because it really is a joint product, the pieces do not become so immersed within internal debates that they become contributions to their disciplines at the expense of making a broad and coherent argument. This...

Objectivity in Science

Objectivity is a cornerstone of science. Bias can erode objectivity when unwittingly introduced into the reporting and teaching of discoveries and theories. This is evident in articles and books on evolution today and may contribute to difficulties in the acceptance of evolution by many supporters of intelligent design. Science has not yet developed to the point of being able to assign purpose to activities in the natural world. In fact, it may never develop to that level. Yet purpose is often implied in descriptions of DNA replication, and this introduces bias. Scientists generally agree that there is no purpose in evolution. The evolutionary process moves along as a result of interactions among and between components of various levels of organization: populations, organisms, molecules, atoms, and subatomic particles and waves. If purpose does exist, its discovery is outside the realm of science at this time. Describing the production of a mutation, such as a DNA strand with a base sequence not complementary to the template strand at each base point, as an “error” or “mistake” unwittingly ascribes purpose to the process. It introduces the assumption that a new strand is “supposed” to be complementary to the template strand at each base point. Such a biased assumption is outside the realm of science. One could just as easily assume that a new complementary strand is not supposed to be an exact complement, but rather a source of variation. This assumption is also outside the realm of science. Base-pairing during replication occurs as a result of natural attractions and repulsions between partially charged components of the bases. This is true if the new strand becomes an inexact complement just as much as it is true if the new strand becomes an exact complement. An inexact complement should not be considered a “mistake.” This may appear trivial at first glance, because scientists often communicate among themselves informally, using purposeful language while not intending a literal interpretation (e.g., elements try to achieve an outer octet of electrons). The danger lies, however, in the use of such informal language in articles and books intended for nonscientists, including textbooks used in high schools and colleges. When mutations are not presented as natural phenomena, but rather as “mistakes,” it becomes difficult for a nonscientist to view them objectively. Many supporters of intelligent design find discomfort in the concept that humans have evolved as a result of “mistakes.” Although it is not an obligation of scientists to address discomfort in concepts, it is an obligation of scientists to present findings in an objective, scientific manner. Presenting mutations as “mistakes” should not be avoided due to any discomfort that may occur. Presenting mutations as “mistakes” should be avoided simply because such a presentation does unwittingly introduce purpose, and hence bias, to the concept. People being presented with the case for evolution should be allowed to evaluate objective arguments, without having first to overcome what they may consider a negative bias, when that bias should not have been introduced in the first place.