Measurement of work group diversity

Whilst research on work group diversity has proliferated in recent years, relatively little attention has been paid to the precise definition of diversity or its measurement. One of the few studies to do so is Harrison and Klein’s (2007) typology, which defined three types of diversity – separation, variety and disparity – and suggested possible indices with which they should be measured. However, their typology is limited by its association of diversity types with variable measurement, by a lack of clarity over the meaning of variety, and by the absence of a clear guidance about which diversity index should be employed. In this thesis I develop an extended version of the typology, including four diversity types (separation, range, spread and disparity), and propose specific indices to be used for each type of diversity with each variable type (ratio, interval, ordinal and nominal). Indices are chosen or derived from first principles based on the precise definition of the diversity type. I then test the usefulness of these indices in predicting outcomes of diversity compared with other indices, using both an extensive simulated data set (to estimate the effects of mis-specification of diversity type or index) and eight real data sets (to examine whether the proposed indices produce the strongest relationships with hypothesised outcomes). The analyses lead to the conclusion that the indices proposed in the typology are at least as good as, and usually better than, other indices in terms of both measuring effect sizes and power to find significant results, and thus provide evidence to support the typology. Implications for theory and methodology are discussed.

Man, I feel like a woman:when and how gender-role motivation helps mind-reading

Two experiments were undertaken with 3 goals: (a) to determine whether manipulating the desirability of including empathy as part of one's gender-role identity motivates accurate mind-reading, (b) to ascertain whether target readability moderates the strength of this effect, and (c) to test whether these effects are mediated by the complexity of perceivers' inferential strategies. Participants viewed videotapes of 2 couples discussing relationship problems and attempted to infer each partner's thoughts and feelings. Both experiments demonstrated that motivation improved accuracy when male and female perceivers valued the empathy-relevant aspects of the traditional female gender role. However, as predicted, high levels of motivation facilitated the accurate reading of easy targets but not of difficult targets. Several mediational models were tested, the results of which showed that the complexity of perceivers' attributions mediated the link between motivation and mind-reading accuracy.

The mosaic test:measuring the effectiveness of colour-based image retrieval

A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants. © 2012 Springer Science+Business Media, LLC.

TEST:a tropic, embodied, and situated theory of cognition

TEST is a novel taxonomy of knowledge representations based on three distinct hierarchically organized representational features: Tropism, Embodiment, and Situatedness. Tropic representational features reflect constraints of the physical world on the agent's ability to form, reactivate, and enrich embodied (i.e., resulting from the agent's bodily constraints) conceptual representations embedded in situated contexts. The proposed hierarchy entails that representations can, in principle, have tropic features without necessarily having situated and/or embodied features. On the other hand, representations that are situated and/or embodied are likely to be simultaneously tropic. Hence, although we propose tropism as the most general term, the hierarchical relationship between embodiment and situatedness is more on a par, such that the dominance of one component over the other relies on the distinction between offline storage versus online generation as well as on representation-specific properties. © 2013 Cognitive Science Society, Inc.

An investigation of the hot-torsion test used in studies of hot workability

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StatNote 38 : The sign test

The sign test is a simple non-parametric test which can be used on paired data, i.e., two related samples, matched samples, or repeated measurements on the same sample. It was developed by Wilcoxon before the more powerful and familiar ‘Wilcoxon signed-rank test’ described in a previous statnote . This statnote describes the use of the sign test with reference to two scenarios: (1) to compare the cleanliness of two hospital wards as assessed by a sample of observers and (2) to compare bacterial contamination on cloths and sponges from a domestic kitchen.

Isothermal fatigue of an aluminide-coated single-crystal superalloy:Part I

The isothermal fatigue behavior of a high-activity aluminide-coated single-crystal superalloy was studied in air at test temperatures of 600 °C, 800 °C, and 1000 °C. Tests were performed using cylindrical specimens under strain control at ∼0.25 Hz; total strain ranges from 0.5 to 1.6 pet were investigated. At 600 °C, crack initiation occurred at brittle coating cracks, which led to a significant reduction in fatigue life compared to the uncoated alloy. Fatigue cracks grew from the brittle coating cracks initially in a stage II manner with a subsequent transition to crystallographic stage I fatigue. At 800 °C and 1000 °C, the coating failed quickly by a fatigue process due to the drastic reduction in strength above 750 °C, the ductile-brittle transition temperature. These cracks were arrested or slowed by oxidation at the coating-substrate interface and only led to a detriment in life relative to the uncoated material for total strain ranges of 1.2 pet and above 800 °C. The presence of the coating was beneficial at 800 °C for total strain rangesless than 1.2 pet. No effect of the coating was observed at 1000 °C. Crack growth in the substrate at 800 °C was similar to 600 °C; at 1000 °C, greater plasticity and oxidationrwere observed and cracks grew exclusively in a stage II manner.

Class I T-cell epitope prediction:improvements using a combination of proteasome cleavage, TAP affinity, and MHC binding

Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.