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The explosion of attention to measuring and understanding implicit bias has been influential inside and outside the academy. The purpose of this chapter is to balance the conversation about how to unpack and understand implicit bias, with an exploration of what we know about Whites’ explicit bias, and how surveys and other data can be used to measure it. This chapter begins with a review of survey-based data on White racial attitudes that reveal complex trends and patterns, with some topics showing changes for the better, but others showing persistent negative or stagnant trends. Drawing on examples using a variety of methodological tools, including (1) traditional survey questions; (2) survey-based mode/question wording experiments; (3) open-ended questions embedded in surveys; and (4) in-depth interviews, I illustrate what explicit racial biases can look like, and how they might be consequential. I argue that a full understanding of intergroup relations requires sophisticated methods and theories surrounding both explicit and implicit biases, how they function separately and in combination, and their causes and consequences.
A key objective for upcoming surveys, and when re-analysing archival data, is the identification of variable stellar sources. However, the selection of these sources is often complicated by the unavailability of light curve data. Utilising a self-organising map (SOM), we demonstrate the selection of diverse variable source types from a catalogue of variable and non-variable SDSS Stripe 82 sources whilst employing only the median $u-g$, $g-r$, $r-i$, and $i-z$ photometric colours for each source as input, without using source magnitudes. This includes the separation of main sequence variable stars that are otherwise degenerate with non-variable sources ($u-g$,$g-r$) and ($r-i$,$i-z$) colour-spaces. We separate variable sources on the main sequence from all other variable and non-variable sources with a purity of $80.0\%$ and completeness of $25.1\%$, figures which can be modified depending on the application. We also explore the varying ability of the same method to simultaneously select other types of variable sources from the heterogeneous sample, including variable quasars and RR-Lyrae stars. The demonstrated ability of this method to select variable main sequence stars in colour-space holds promise for application in future survey reduction pipelines and for the analysis of archival data, where light curves may not be available or may be prohibitively expensive to obtain.
This chapter introduces a research design to study the effects of community policing. The chapter introduces the Metaketa model of multi-site trials, which are used to answer questions relevant to policy using coordinated experiments in which the same intervention is randomly assigned to units in multiple contexts and the same outcomes are measured to estimate effects. In specific, the chapter introduces how the six countries were selected for study and describes their characteristics in terms of crime and policing and then how the interventions were selected and harmonized across the settings and how they compare to community policing policies in the world. The remainder of the chapter details the experimental design, from how police beats and units are sampled, how community policing intervention was randomly assigned, how outcomes were measured and harmonized, how effects were estimated for each site and then averaging across sites, and how we planned to address threats to inference.
Once the theory is specified and an operationalization has been chosen for the nodes and links, the next step is to acquire the data. This chapter goes deep into issues that arise when designing surveys to collect data. Although this is not the only method of data collection, it is one that illuminates issues that pertain to all others. This chapter covers the practical question of how to use surveys to elicit network information. The advice leans heavily on a well-formulated theory.
The importance of simple descriptive data was recognised by William Farr, whom we mentioned briefly in Chapter 1 for his seminal work using the newly established vital statistics register of England in the nineteenth century. As we discussed in Chapter 1, this descriptive epidemiology, concerned as it is with ‘person, place and time’, attempts to answer the questions ‘Who?’, ‘What?’, ‘Where?’ and ‘When?’. This can include anything from a description of disease in a single person (a case report) or a special survey conducted to measure the prevalence of a particular health issue in a specific population, to reports from national surveys and data collection systems showing how rates of disease or other health-related factors vary in different geographical areas or over time (time trends). In this chapter we look in more detail at some of the most common types of descriptive data and where they come from. However, before embarking on a data hunt, we first need to decide exactly what it is we want to know, and this can pose a challenge. To make good use of the most relevant descriptive data, it is critical to formulate our question as precisely as possible.
Taking a simplified approach to statistics, this textbook teaches students the skills required to conduct and understand quantitative research. It provides basic mathematical instruction without compromising on analytical rigor, covering the essentials of research design; descriptive statistics; data visualization; and statistical tests including t-tests, chi-squares, ANOVAs, Wilcoxon tests, OLS regression, and logistic regression. Step-by-step instructions with screenshots are used to help students master the use of the freely accessible software R Commander. Ancillary resources include a solutions manual and figure files for instructors, and datasets and further guidance on using STATA and SPSS for students. Packed with examples and drawing on real-world data, this is an invaluable textbook for both undergraduate and graduate students in public administration and political science.
This paper distinguishes news about short-lived events from news about changes in longer term prospects using surveys of expectations. Employing a multivariate GARCH-in-Mean model for the US, the paper illustrates how the different types of news influence business cycle dynamics. The influence of transitory output shocks can be relatively large on impact but gradually diminishes over two to three years. Permanent shocks drive the business cycle, generating immediate stock price reactions and gradually building output effects, although they have more immediate output effects during recessions through the uncertainties they create. Markedly different macroeconomic dynamics are found if these explicitly identified types of news or uncertainty feedbacks are omitted from the analysis.
Chapter 2 covers the period in the late 1960s and early 1970s when the Brazilian military government planned and began building its big dams. It argues that political pressures encouraged the military regime to build dams with giant reservoirs and to do so quickly and without regard to their social and environmental footprints. The dictatorship looked to hydropower projects as a means of powering industrial and economic growth that would legitimize military rule, and it wasted no time in starting construction because it takes a long time to build big dams, often the better part of a decade, and sometimes longer. The 1973 oil crisis added urgency, raising the price of imported petroleum and pushing the government to invest in alternative sources of energy. The crisis encouraged the military regime to double down on the big dams already under construction and to plan a host of new ones. Political pressures also made their way into debates about specific dam sites. The most prominent case was the binational Itaipu Dam (on the Brazilian-Paraguayan Border), where the military government had to weigh geopolitical considerations alongside other criteria. The result of all these political pressures combined was a firm commitment to building large reservoirs in environmentally sensitive areas without public debate and without completing thorough environmental impact studies.
In working with network data, data acquisition is often the most basic yet the most important and challenging step. The availability of data and norms around data vary drastically across different areas and types of research. A team of biologists may spend more than a decade running assays to gather a cells interactome; another team of biologists may only analyze publicly available data. A social scientist may spend years conducting surveys of underrepresented groups. A computational social scientist may examine the entire network of Facebook. An economist may comb through large financial documents to gather tables of data on stakes in corporate holdings. In this chapter, we move one step along the network study life-cycle. Key to data gathering is good record-keeping and data provenance. Good data gathering sets us up for future success—otherwise, garbage in, garbage out—making it critical to ensure the best quality and most appropriate data is used to power your investigation.
This chapter tests two ways of overcoming uncertainty about relationality – having potential collaborators directly communicate how they will relate to each other, and using third parties such as matchmakers and boundary spanners. Both are useful for creating valuable new collaborative relationships, especially between people who begin as strangers. In addition, this chapter also presents evidence showing the impact of new collaborative relationships on strategic decision-making. Data in this chapter come from a variety of national surveys, field experiments, and case comparisons.
For the vast majority of us salary is one of the key reasons we work. With bills to pay and mouths to feed we want to know we are being fairly compensated for the jobs we do. One way to check this is to use the BIALL Annual Salary Survey which considers not only salaries but also working conditions and benefits, offering a comparison to similar organisations and roles. In this article Julie Christmas, Claire Mazer and the team from CB Resourcing highlight some of the findings from the 2023 survey and consider the reasons behind these.
Survey experiments often yield intention-to-treat effects that are either statistically and/or practically “non-significant.” There has been a commendable shift toward publishing such results, either to avoid the “file drawer problem” and/or to encourage studies that conclude in favor of the null hypothesis. But how can researchers more confidently adjudicate between true, versus erroneous, nonsignificant results? Guidance on this critically important question has yet to be synthesized into a single, comprehensive text. The present essay therefore highlights seven “alternative explanations” that can lead to (erroneous) nonsignificant findings. It details how researchers can more rigorously anticipate and investigate these alternative explanations in the design and analysis stages of their studies, and also offers recommendations for subsequent studies. Researchers are thus provided with a set of strategies for better designing their experiments, and more thoroughly investigating their survey-experimental data, before concluding that a given result is indicative of “no significant effect.”
Chapter 6 presents an array of techniques for assessing motivation including self-reports, questionnaires, rating scales, checklists, surveys, interviews, and a diagnostic protocol. In addition to these assessments, Appendices 6A, 6B, and 6C – designed for teachers, students, and corporate folk – contain the Reisman Diagnostic Motivation Assessment (RDMA) items that emerged from and are categorized by the motivation theorists presented in Chapter 3. Appendix 6D includes the Reisman Diagnostic Creativity Assessment (RDCA) interpretation and Appendix 6E provides an alternative RDMA interpretation. This chapter also addresses why motivation in education is important, students and motivation, teachers and motivation, corporate employer and employee motivation, self-esteem and motivation, and motivation and creativity.
The Australian SKA Pathfinder (ASKAP) has surveyed the sky at multiple frequencies as part of the Rapid ASKAP Continuum Survey (RACS). The first two RACS observing epochs, at 887.5 (RACS-low) and 1 367.5 (RACS-mid) MHz, have been released (McConnell, et al. 2020, PASA, 37, e048; Duchesne, et al. 2023, PASA, 40, e034). A catalogue of radio sources from RACS-low has also been released, covering the sky south of declination $+30^{\circ}$ (Hale, et al., 2021, PASA, 38, e058). With this paper, we describe and release the first set of catalogues from RACS-mid, covering the sky below declination $+49^{\circ}$. The catalogues are created in a similar manner to the RACS-low catalogue, and we discuss this process and highlight additional changes. The general purpose primary catalogue covering 36 200 deg$^2$ features a variable angular resolution to maximise sensitivity and sky coverage across the catalogued area, with a median angular resolution of $11.2^{\prime\prime} \times 9.3^{\prime\prime}$. The primary catalogue comprises 3 105 668 radio sources, including those in the Galactic Plane (2 861 923 excluding Galactic latitudes of $|b|<5^{\circ}$), and we estimate the catalogue to be 95% complete for sources above 2 mJy. With the primary catalogue, we also provide two auxiliary catalogues. The first is a fixed-resolution, 25-arcsec catalogue approximately matching the sky coverage of the RACS-low catalogue. This 25-arcsec catalogue is constructed identically to the primary catalogue, except images are convolved to a less-sensitive 25-arcsec angular resolution. The second auxiliary catalogue is designed for time-domain science and is the concatenation of source lists from the original RACS-mid images with no additional convolution, mosaicking, or de-duplication of source entries to avoid losing time-variable signals. All three RACS-mid catalogues, and all RACS data products, are available through the CSIRO ASKAP Science Data Archive (https://research.csiro.au/casda/).
The main quantitative research designs are reviewed, to indicate their strengths and limitations. Even the best designed and conducted studies run the risk of being influenced by the ever-present threats of chance, bias, and confounding, terms that are explained and illustrated with examples, and of sampling and measurement error. The informed reader should therefore look beyond the results of a study, using critical appraisal skills to ask whether the study’s design, sample, and measures are robust enough to allow the findings to be taken as likely to be accurate.
We present observations of the Mopra carbon monoxide (CO) survey of the Southern Galactic Plane, covering Galactic longitudes spanning $l = 250^{\circ}$ ($-110^{\circ}$) to $l = 355^{\circ}$ ($-5^{\circ}$), with a latitudinal coverage of at least $|b|<1^\circ$, totalling an area of $>$210 deg$^{2}$. These data have been taken at 0.6 arcmin spatial resolution and 0.1 km s$^{-1}$ spectral resolution, providing an unprecedented view of the molecular gas clouds of the Southern Galactic Plane in the 109–115 GHz $J = 1-0$ transitions of $^{12}$CO, $^{13}$CO, C$^{18}$O, and C$^{17}$O.
The Australian SKA Pathfinder (ASKAP) is being used to undertake a campaign to rapidly survey the sky in three frequency bands across its operational spectral range. The first pass of the Rapid ASKAP Continuum Survey (RACS) at 887.5 MHz in the low band has already been completed, with images, visibility datasets, and catalogues made available to the wider astronomical community through the CSIRO ASKAP Science Data Archive (CASDA). This work presents details of the second observing pass in the mid band at 1367.5 MHz, RACS-mid, and associated data release comprising images and visibility datasets covering the whole sky south of $\delta_{\text{J2000}}=+49^\circ$. This data release incorporates selective peeling to reduce artefacts around bright sources, as well as accurately modelled primary beam responses. The Stokes I images reach a median noise of 198 $\mu$Jy PSF$^{-1}$ with a declination-dependent angular resolution of 8.1–47.5 arcsec that fills a niche in the existing ecosystem of large-area astronomical surveys. We also supply Stokes V images after application of a widefield leakage correction, with a median noise of 165 $\mu$Jy PSF$^{-1}$. We find the residual leakage of Stokes I into V to be $\lesssim 0.9$–$2.4$% over the survey. This initial RACS-mid data release will be complemented by a future release comprising catalogues of the survey region. As with other RACS data releases, data products from this release will be made available through CASDA.
We offer details of our empirical approach. Our method involved multiple distinct representative surveys of key college athletic stakeholders (i.e., student-athletes, coaches, athletic administrators, and the American public including nonfans and fans). Our surveys measure opinions on a set of gender equity policy proposals (e.g., equal spending, requiring schools to interview at least one woman for athletic director jobs, etc.). We also include an exercise that requires respondents to confront inevitable policy tradeoffs. Respondents are asked to allocate a fixed budget to fund gender equity initiatives or benefit initiatives (e.g., paying college student-athletes versus guaranteed scholarships). Our measures allow us to explore the empirical evidence for our argument while making generalizable statements about the relevant stakeholders. The chapter provides details of our measurement approach and samples, as well as how we connect our theory to our analyses. Our data allow us to excavate important dynamics within and across group that have interests in college athletics.
We present a systematic search for radio counterparts of novae using the Australian Square Kilometer Array Pathfinder (ASKAP). Our search used the Rapid ASKAP Continuum Survey, which covered the entire sky south of declination $+41^{\circ}$ ($\sim$$34000$ square degrees) at a central frequency of 887.5 MHz, the Variables and Slow Transients Pilot Survey, which covered $\sim$$5000$ square degrees per epoch (887.5 MHz), and other ASKAP pilot surveys, which covered $\sim$200–2000 square degrees with 2–12 h integration times. We crossmatched radio sources found in these surveys over a two–year period, from 2019 April to 2021 August, with 440 previously identified optical novae, and found radio counterparts for four novae: V5668 Sgr, V1369 Cen, YZ Ret, and RR Tel. Follow-up observations with the Australian Telescope Compact Array confirm the ejecta thinning across all observed bands with spectral analysis indicative of synchrotron emission in V1369 Cen and YZ Ret. Our light-curve fit with the Hubble Flow model yields a value of $1.65\pm 0.17 \times 10^{-4} \rm \:M_\odot$ for the mass ejected in V1369 Cen. We also derive a peak surface brightness temperature of $250\pm80$ K for YZ Ret. Using Hubble Flow model simulated radio lightcurves for novae, we demonstrate that with a 5$\sigma$ sensitivity limit of 1.5 mJy in 15-min survey observations, we can detect radio emission up to a distance of 4 kpc if ejecta mass is in the range $10^{-3}\rm \:M_\odot$, and upto 1 kpc if ejecta mass is in the range $10^{-5}$–$10^{-3}\rm \:M_\odot$. Our study highlights ASKAP’s ability to contribute to future radio observations for novae within a distance of 1 kpc hosted on white dwarfs with masses $0.4$–$1.25\:\rm M_\odot$, and within a distance of 4 kpc hosted on white dwarfs with masses $0.4$–$1.0\:\rm M_\odot$.