Data Labours: How the Sequence Databases GenBank and EMBL-Bank Make Data

What actually happens inside genetic databases, how do they work upon data and who does this work? While they have become central tools for doing science, not much is known about the work that goes on inside these vital infrastructures. Ethnographic explorations of two of the world’s largest nucleotide sequence databases, GenBank and the European Molecular Biology Laboratory’s EMBL-Bank, reveal manifold goings-on. Like most infrastructural work, it is modest and invisible routines that build and maintain the vast interconnected suite of bioinformational resources. Data curators construct organisms out of sulphuric sludge, dataflow engineers as self-styled “genetic information plumbers” keep the data deluge flowing, and a data submissions support assistant manages to make room for care amidst this deluge. Taken together, these data labours render tangible the modest and processual aspects of data infrastructure while also revealing the databases to be situated and lively spaces of convergence. Inventively analysing data labours paves surprising ways for encountering and making sense of databases, data and the work they do. Here, practices of natural history, like specimen-making and curation, are continued by other means while the assembly of sludge sheds light on the absences and deletions which mystify infrastructural maintenance work.     

Rising High or Falling Deep? Pathways of Self‐Esteem in a Representative German Sample

In many longitudinal studies, self‐esteem has been shown to increase up until around age 50 or 60 and to decrease thereafter. These studies have also found substantial inter‐individual differences in the intra‐individual development of self‐esteem. In the current study, we examined whether this variation in change could be attributed to underlying latent classes of individuals following different trajectories of self‐esteem development over time. By applying general growth mixture modelling to data from the representative German pairfam study (N = 12 377), four latent classes of self‐esteem development across five years were extracted. Based on their mean levels, trajectories, and variability, individuals in the latent classes could be described as having (a) constant and stable high self‐esteem (29.00% of the sample), (b) constant but variable moderate self‐esteem (31.69%), (c) increasing and stabilizing self‐esteem (15.13%), and (d) decreasing and variable self‐esteem (24.18%). Furthermore, these latent classes differed in accordance with findings of prior research on self‐rated, partner‐rated, and objective correlates of the domains of health and well‐being, partner relationships, and occupational status. Thus, the current study shows that inter‐individual variation in intra‐individual change in self‐esteem is not random but reflects specific individual trajectories, or pathways, of self‐esteem. Copyright © 2016 European Association of Personality Psychology     

Lessons learned from using shadowing as a qualitative research technique in Education

While shadowing is known in disciplines such as Organizational Studies, there is little reference to shadowing as a qualitative research technique in Education or other social science fields. This paper explores shadowing in the research literature and my experience collecting data using shadowing. Using my researcher journal and reflections, I present five lessons learned as a qualitative shadowing researcher in Education: shadowing is difficult, tiring and time consuming; shadowing is high stakes emotionally for the participants; participants have control during data collection, researchers have control with the results; shadowing researchers must manage relationships with the participants; and ethics in shadowing can be murky and researchers must make continuous ethical judgements while in the field.     

Logit models and logistic regressions for social networks: I. An introduction to Markov graphs andp

Spanning nearly sixty years of research, statistical network analysis has passed through (at least) two generations of researchers and models. Beginning in the late 1930's, the first generation of research dealt with the distribution of various network statistics, under a variety of null models. The second generation, beginning in the 1970's and continuing into the 1980's, concerned models, usually for probabilities of relational ties among very small subsets of actors, in which various simple substantive tendencies were parameterized. Much of this research, most of which utilized log linear models, first appeared in applied statistics publications.But recent developments in social network analysis promise to bring us into a third generation. The Markov random graphs of Frank and Strauss (1986) and especially the estimation strategy for these models developed by Strauss and Ikeda (1990; described in brief in Strauss, 1992), are very recent and promising contributions to this field. Here we describe a large class of models that can be used to investigate structure in social networks. These models include several generalizations of stochastic blockmodels, as well as models parameterizing global tendencies towards clustering and centralization, and individual differences in such tendencies. Approximate model fits are obtained using Strauss and Ikeda's (1990) estimation strategy.In this paper we describe and extend these models and demonstrate how they can be used to address a variety of substantive questions about structure in social networks.This research was supported by grants from the Australian Research Council and the National Science Foundation (#SBR93-10184). This paper was presented at the 1994 Annual Meeting of the Psychometric Society, Champaign, Illinois, June 1994. Special thanks go to Sarah Ardu for programming assistance, Laura Koehly and Garry Robins for help with this research, and to Shizuhiko Nishisato and three reviewers for their comments. INTERNETemail addresses:pattison@psych.unimelb.edu.au (PP);stanwass@uiuc.edu (SW). Affiliations: Department of Psychology, University of Melbourne (PP); Department of Psychology, Department of Statistics, and The Beckman Institute for Advanced Science and Technology, University of Illinois (SW).     

Psychometric assessment of cardiac transplantation candidates

Psychometric assessment protocols were used to chart the course of 287 end-stage cardiac patients' psychological adjustment at pretransplantation and, again, in 34 who were subsequently transplanted. The regression and repeated-measures analyses suggested that psychological distress is typical of the adult transplantation candidate, although impaired cognitive functioning is more typical of the acute postoperative stage. Negative affect, cognitive, personality, and coping measures are interrelated at pretransplantation; depression and mental control show significant decreases at 2 weeks posttransplantation. Whereas the transplantation process is inherently distressing, psychological testing may identify cognitive and personality features that require more specific clinical attention.     

A REVIEW OF ACADEMIC PERMANENT-PRODUCT DATA COLLECTION AND RELIABILITY PROCEDURES IN APPLIED BEHAVIOR ANALYSIS RESEARCH1

Three publication sources were reviewed to determine the recent conventions for collecting, and assessing the reliability of, academic permanent-product data (handwriting, examination papers, etc in applied behavior analysis. The primary source was the Journal of Applied Behavior Analysis (1968–1974). Secondary sources included conference proceedings titled, A new direction in education: behavior analysis (E. Ramp and B. L. Hopkins, Eds., Lawrence, Kansas: Support and Development Center for Follow Through, Department of Human Development, University of Kansas, 1971), and Behavior Analysis and Education (G. Semb, Ed., Lawrence, Kansas: Support and Development Center for Follow Through, Department of Human Development, University of Kansas, 1972). Finally, as a test of the generality of the findings in the two applied behavior analysis sources, the current issue of each of 14 psychological and/or educational journals was reviewed. Thirty JABA studies reported academic permanent-product data, but only 14 reported reliability. Increasingly more product data through 1973 have been reported along with a greater proportion of authors reporting reliability. The review of the two conference proceeding publications revealed the same trend. In 1971, only three studies reported academic product data, none with reliability, while in 1972, 15 reported academic data, nine including reliability assessment. The review of 14 current education/psychology journal issues revealed four studies reporting academic data, none with reliability. Across all sources, about one-half of the studies reported reliability. Most of the studies reporting reliability described the frequency of reliability assessment, with approximately equal numbers of JABA studies reporting reliability for each paper or reliability for each session. The use of uninformed observers was reported in only three JABA studies and one conference study. Marks made on subjects' papers by either the teacher or the primary observer were reported masked for reliability purposes by only two JABA and two conference studies. Reliability was calculated on a session total basis in two JABA studies. Point-by-point agreement was given in nine JABA and three conference studies. Perfect reliability (mean agreement of 100%) was reported in only six JABA and three conference studies. Scores between 90 and 100% were reported in nine JABA and four conference studies. Scores below 80% were reported in three JABA studies. No other percentage agreement scores were reported, although one JABA study reported correlational reliability (Pearson r). In summary, recently more studies have dealt with academic data and, until 1974, a greater proportion of these studies reported reliability assessment, and relatively few studies reported either replicable methods, 100% agreement, or controls for maintaining rater independence.