Organizational Memory as Objects, Processes, and Trajectories: An Examination of Organizational Memory in Use

For proper knowledge management, organizations must consider how knowledge is kept and reused. The term organizational memory is due for an overhaul. Memory appears to be everywhere in organizations; yet, the term has been limited to only a few uses. Based on an ethnographic study of a telephone hotline group, this paper presents a micro-level, distributed cognition analysis of two hotline calls, the work activity surrounding the calls, and the memory used in the work activity. Drawing on the work of Star, Hutchins, and Strauss, the paper focuses on issues of applying past information for current use. Our work extends Strauss' and Hutchins' trajectories to get at the understanding of potential future use by participants and its role in current information storage. We also note the simultaneously shared provenance and governance of multiple memories – human and technical. This analysis and the theoretical framework we construct should be to be useful in further efforts in describing and analyzing organizational memory within the context of knowledge management efforts.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42609/1/10606_2004_Article_DO00000135.pd

Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants

A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci

Genome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma (MM)

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.BCAC is funded by Cancer Research UK (C1287/A10118, C1287/A12014) and by the European Community's Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS). Meetings of the BCAC have been funded by the European Union COST programme (BM0606). Genotyping on the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710, C8197/A16565), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer program and the Ministry of Economic Development, Innovation and Export Trade of Quebec, grant PSR-SIIRI-701. Combination of the GWAS data was supported in part by the US National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative, grant 1 U19 CA148065-01 (DRIVE, part of the GAME-ON initiative). For a full description of funding and acknowledgments, see the Supplementary Note.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.324

The Redshift Evolution of the Mean Temperature, Pressure, and Entropy Profiles in 80 SPT-Selected Galaxy Clusters

We present the results of an X-ray analysis of 80 galaxy clusters selected in the 2500 deg2 South Pole Telescope survey and observed with the Chandra X-ray Observatory. We divide the full sample into subsamples of ∼20 clusters based on redshift and central density, performing a joint X-ray spectral fit to all clusters in a subsample simultaneously, assuming self-similarity of the temperature profile. This approach allows us to constrain the shape of the temperature profile over 0 R500) regions than their low-z (0.3 < z < 0.6) counterparts. Combining the average temperature profile with measured gas density profiles from our earlier work, we infer the average pressure and entropy profiles for each subsample. Confirming earlier results from this data set, we find an absence of strong cool cores at high z, manifested in this analysis as a significantly lower observed pressure in the central 0.1R500 of the high-z cool-core subset of clusters compared to the low-z cool-core subset. Overall, our observed pressure profiles agree well with earlier lower-redshift measurements, suggesting minimal redshift evolution in the pressure profile outside of the core. We find no measurable redshift evolution in the entropy profile at r . 0.7R500 – this may reflect a long-standing balance between cooling and feedback over long timescales and large physical scales. We observe a slight flattening of the entropy profile at r & R500 in our high-z subsample. This flattening is consistent with a temperature bias due to the enhanced (∼3×) rate at which group-mass (∼2 keV) halos, which would go undetected at our survey depth, are accreting onto the cluster at z ∼ 1. This work demonstrates a powerful method for inferring spatially-resolved cluster properties in the case where individual cluster signal-to-noise is low, but the number of observed clusters is high.Physic

Distributed Cognition as a Theoretical Framework for HCI: Don&apos;t Throw the Baby Out With the Bathwater - The Importance of the Cursor in Air Traffic Control

this report are available for $5.00 each from the Department of Cognitive Science, UCSD, La Jolla, CA 92093-0515. A PostScript version of this report is available by anonymous ftp from cogsci.ucsd.edu in /pub/tr. Copyright 1994 by Christine A. Halverson. Distributed Cognition as a Theoretical Framework for HCI: Don&apos;t Throw the Baby out with the Bathwater --the Importance of the Cursor in Air Traffic Control 1 Christine A. Halverson Department of Cognitive Science, 0515 University of California, San Diego 9500 Gilman Drive La Jolla CA, 92093-0515 USA email: [email protected] PH: 619-534-4348 FAX: 619-534-1128 Introduction Two of the roles of theory in human computer interaction (HCI) are to aid design and analysis. However, theories can often be unwieldy in their application. Thus the demonstration of a particular theory in application to a problem in HCI may be the best demonstration of that theory&apos;s utility. In this paper, I present the theory of distributed cognition and apply it to the analysis of an automation tool for air traffic control (ATC). This example demonstrates how: 1) the theory of distributed cognition influences and informs every step of the process of analysis and redesign; 2) any interaction is embedded in a domain and thus a socio-cultural context that must be considered; and 3) that understanding what to retain of an existing design is as important as the evaluation of enhancements. 1 Originally presented as a position paper for the InterCHI &apos;93 Workshop -- Rethinking Theoretic Frameworks for Human-Computer Interaction. Yvonne Rogers, Liam Bannon, and Grahm Button, Chairs. Research support was provided by cooperative agreement NCC2-591 to Edwin Hutchins from the Ames Research Center of the National Aeronautics and Space Administration (NASA..

Activity Theory and Distributed Cognition: Or What Does CSCW Need to DO with Theories?

This essay compares activity theory (AT) with distributed cognition theory (DCOG), asking what each can do for CSCW. It approaches this task by proposing that theories – when viewed as conceptual tools for making sense of a domain – have four important attributes: descriptive power; rhetorical power; inferential power; and application power. It observes that AT and DCOG are not so different: both emphasize cognition; both include the social and cultural context of cognition; both share a commitment to ethnographically collected data. Starting with a description of the distributed cognition approach, it uses an example of a DCOG analysis to ground a discussion of the strengths and weaknesses of AT and DCOG as an approach to issues in CSCW. Finally, the essay considers what theoretical work is being done by the attributes of the respective theories, and whether AT, DCOG, or any theory developed outside the context of group work, will work for CSCW

or What

Activity theory and distributed cognition