We seek to understand how the experiences of groups that differ in gender, ethnicity, and sexual orientation produce college-level educational performances that differ from the experiences of the dominant majority group. We employ two datasets: a National Database of 24,701 participants and a Paired-Measures Database with 3,323 participants. Both datasets provide demographic information, socioeconomic conditions of status as first-generation student, English as a first language, and interest in majoring in science, and competency scores on understanding science as a way of knowing obtained from the Science Literacy Concept Inventory. The Paired-Measures Database includes additional selfassessed competence ratings that enabled quantifying affective confidence. We meld the ways of knowing of ethics, numeracy, and social justice, especially the social justice concept of Othering, to interpret our data. Two of three competing hypotheses about self-assessment encourage Othering. Our data strongly support the third-that all groups are good at self-assessment and merit equal respect. Women and men are equally competent in science literacy. Women, on average, are more accurate in their self-assessments whereas men, on average, are overconfident. Those with minority sexual orientations register higher competence than the binary-sexual majority but are less confident of their competency. Minority ethnicities, on average, produce significantly lower science literacy scores. With one exception (Middle Eastern), groups produce mean self-assessed competence ratings that are remarkably accurate predictors of their mean competence scores. The three socioeconomic conditions exert significant and unequal impacts across ethnic groups, with Hispanic, Middle Eastern and Pacific Islander data providing some unique results.

Cogan, C. B., Todd, B. J., Lawton, P., and Noji, T. T. 2009. The role of marine habitat mapping in ecosystem-based management. – ICES Journal of Marine Science, 66: 2033–2042. Ecosystem-based management (EBM) and the related concept of large marine ecosystems (LMEs) are sometimes criticized as being too broad for many management and research applications. At the same time, there is a great need to develop more effectively some substantive scientific methods to empower EBM. Marine habitat mapping (MHM) is an example of an applied set of field methods that support EBM directly and contribute essential elements for conducting integrated ecosystem assessments. This manuscript places MHM practices in context with biodiversity models and EBM. We build the case for MHM being incorporated as an explicit and early process following initial goal-setting within larger EBM programmes. Advances in MHM and EBM are dependent on evolving technological and modelling capabilities, conservation targets, and policy priorities within a spatial planning framework. In both cases, the evolving and adaptive nature of these sciences requires explicit spatial parameters, clear objectives, combinations of social and scientific considerations, and multiple parameters to assess overlapping viewpoints and ecosystem functions. To examine the commonalities between MHM and EBM, we also address issues of implicit and explicit linkages between classification, mapping, and elements of biodiversity with management goals. Policy objectives such as sustainability, ecosystem health, or the design of marine protected areas are also placed in the combined MHM–EBM context.

After articulating 12 concepts for the reasoning component of citizen-level science literacy and restating these as assessable student learning outcomes (SLOs), we developed a valid and reliable assessment instrument for addressing the outcomes with a brief 25-item science literacy concept inventory (SLCI). In this paper, we report the results that we obtained from assessing the citizen-level science literacy of 17,382 undergraduate students, 149 graduate students, and 181 professors. We address only findings at or above the 99.9% confidence level. We found that general education (GE) science courses do not significantly advance understanding of science as a way of knowing. However, the understanding of science’s way of knowing does increase through academic ranks, indicating that the extended overall academic experience better accounts for increasing such thinking capacity than do science courses alone. Higher mean institutional SLCI scores correlate closely with increased institutional selectivity, as measured by the institutions’ higher mean SAT and ACT scores. Socioeconomic factors of a) first-generation student, b) English as a native language, and c) interest in commitment to a science major are unequally distributed across ethnic groups. These factors proved powerful in accounting for the variations in SLCI scores across ethnicities and genders.

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Despite nearly two decades of research, researchers have not resolved whether people generally perceive their skills accurately or inaccurately. In this paper, we trace this lack of resolution to numeracy, specifically to the frequently overlooked complications that arise from the noisy data produced by the paired measures that researchers employ to determine self-assessment accuracy. To illustrate the complications and ways to resolve them, we employ a large dataset (N = 1154) obtained from paired measures of documented reliability to study self-assessed proficiency in science literacy. We collected demographic information that allowed both criterion-referenced and normative-based analyses of selfassessment data. We used these analyses to propose a quantitatively based classification scale and show how its use informs the nature of self-assessment. Much of the current consensus about peoples' inability to self-assess accurately comes from interpreting normative data presented in the Kruger-Dunning type graphical format or closely related (y -x) vs. (x) graphical conventions. Our data show that peoples' self-assessments of competence, in general, reflect a genuine competence that they can demonstrate. That finding contradicts the current consensus about the nature of self-assessment. Our results further confirm that experts are more proficient in self-assessing their abilities than novices and that women, in general, self-assess more accurately than men. The validity of interpretations of data depends strongly upon how carefully the researchers consider the numeracy that underlies graphical presentations and conclusions. Our results indicate that carefully measured self-assessments provide valid, measurable and valuable information about proficiency.