1931年；陈伯华沙市崭露头角

汉剧艺术大师陈伯华从艺60年，集花旦青衣之精华，创立了风格独具的“陈派”艺术，树立起汉剧艺术的里程碑，而她崭露头角之地却是湖北沙市，说来还有一段故事。     

2007,图书市场谁领风骚?

在商业社会,在自由竞争的市场上,出版畅销书往往成为有意识的商业行为,而且会有基于销量统计的比较准确客观的排行榜证明它的成功.     

微软与思科,暧昧2007

两大巨头的竞争与合作,都是这个领域寻求双赢的结果。一个是软件行业的巨人,一个是通信领域的王者。如果非要将他们来一次对抗的话,那宛若激烈拼杀的足球场上来了一个篮球运动员,比赛又     

2007,我们到哪里买房

怎么又说房子?问题解决不了、解决不好就永远是问题。视之所见、听之所闻,我们自己、我们周围的朋友、我们朋友的朋友,连年以来是怎样地为房子的问题所困扰啊。无房而为买房愁,有房而为还款愁,自己这一代好歹有房了,又不得不给下一代考虑。祖宗传下来人生4件大烦事:吃穿住行,现     

略论1931年的南京水灾救助

1931年,江淮流域爆发了规模空前的水灾,首都南京亦不能幸免.作为“首善之区”,南京的水灾救助得到了各方的高度重视,无论是各级政府机关,还是临时成立的、注意吸收社会力量的各种救灾组织,都在其中发挥了积极作用.围绕着赈灾物资的发放、灾民收容与遣散、灾时卫生防疫以及工赈、农赈等救助措施,救灾力量形成了合作与互补的关系,一方面尽可能地减少了水灾对灾民造成的伤害,另一方面则为国家救灾机制的完善提供了契机.     

2007,假新闻泛滥的五大成因

一、片面追求轰动效果市场竞争激烈,一些媒体为了吸引受众,就采用最方便也是最有效的方法——发表有炒作价值的新闻。这些新闻多是追求轰动效应、争奇猎怪之作。有不少假新闻,记者和编辑只要多花点工夫核实一下,很容易发现漏洞,但是出于“抢新闻”的考虑,宁愿先登出来再去追踪求证。比如,《美国枪击32名大学生案凶手为中国人》的假新闻。去年4月16日,美国历史上最严重的校园枪击案发生,第二天中国新闻网发布来自纽约的消息,称“发生在弗吉尼亚理工大学的特大枪案凶嫌身份初步认定：     

2007,鲁媒的合纵与突围

随着2004年中国媒体政策的调整，山东21种县（市）报停办，3种划转，2种被保留的实行有偿兼并；期刊类有18种停办，7种管办分离，5种划转，5种合并，1种保留。此后，进入了一个新格局的调整阶段，三年过后，媒体大多完成了整合阶段，在整合过程中，合纵和各种形式下的突围成了近期山东媒体的主要特征。     

中国抗战十四年：1931～1945

抓_班 少咖补且如常一椒的连续轰时f盼侧“滩补李娜势未久姗、如年砖1 日军发动了更只. 产月创日至~8月邵日井4打七.对勇庆飞史炸冈次 夕泣 以粉烈杯记徽粼粉濒成.:践冲沙左洲钟 计幸拐气 Jl 、卜川沐 介伙 百玄含“ ,:、{: 之争挂者 ); 勺 19二{1‘ rgJS卒1刀,成于上二 民区.犷937丰招月 严万动段, 准 ,93,卒9月活日奋,日军以其制造的.却亲砌(沟)事件“为I”7年7月7日。日军均击宛乎桩.进玫卢沟桥.中 借口,大举班玫沈用.这是B军在沈阳城场上向中国军以进玫。国守军第29军吉星戈团左卢沟桥上奋起班抗。 19J7卒12月护J日. 日军望占南京后.…     

An analysis of bibliometric indicators,National Institutes of Health funding,and faculty size at Association of American Medical Colleges medical schools, 1997–2007

Objective:

The objective of this study was to analyze bibliometric data from ISI, National Institutes of Health (NIH)–funding data, and faculty size information for Association of American Medical Colleges (AAMC) member schools during 1997 to 2007 to assess research productivity and impact.

Methods:

This study gathered and synthesized 10 metrics for almost all AAMC medical schools (n = 123): (1) total number of published articles per medical school, (2) total number of citations to published articles per medical school, (3) average number of citations per article, (4) institutional impact indices, (5) institutional percentages of articles with zero citations, (6) annual average number of faculty per medical school, (7) total amount of NIH funding per medical school, (8) average amount of NIH grant money awarded per faculty member, (9) average number of articles per faculty member, and (10) average number of citations per faculty member. Using principal components analysis, the author calculated the relationships between measures, if they existed.

Results:

Principal components analysis revealed 3 major clusters of variables that accounted for 91% of the total variance: (1) institutional research productivity, (2) research influence or impact, and (3) individual faculty research productivity. Depending on the variables in each cluster, medical school research may be appropriately evaluated in a more nuanced way. Significant correlations exist between extracted factors, indicating an interrelatedness of all variables. Total NIH funding may relate more strongly to the quality of the research than the quantity of the research. The elimination of medical schools with outliers in 1 or more indicators (n = 20) altered the analysis considerably.

Conclusions:

Though popular, ordinal rankings cannot adequately describe the multidimensional nature of a medical school''s research productivity and impact. This study provides statistics that can be used in conjunction with other sound methodologies to provide a more authentic view of a medical school''s research. The large variance of the collected data suggests that refining bibliometric data by discipline, peer groups, or journal information may provide a more precise assessment.

Highlights

• Principal components analysis discovered three clusters of variables: (1) institutional research productivity, (2) research influence or impact, and (3) individual faculty research productivity.
• The associations between size-independent measures (e.g., average number of citations/article) were more significant than associations between size-independent bibliometric measures and size-dependent (e.g., number of faculty) bibliometric measures and vice versa, except in the case of total National Institutes of Health (NIH) funding.
• The factor coefficients, or loadings, for total NIH funding may associate more with the quality of research rather than the quantity of research.
• The removal of twenty outliers, fourteen highly productive or influential medical schools and six medical schools with relatively low research profiles, changed the results of the analysis significantly.
• This study''s broad institutional bibliometric data sets cannot be extrapolated to specific departments at the studied medical schools.

Implications

• Librarians, administrators, and faculty should use several methodologies in tandem with bibliometric data when evaluating institutions'' research impact and productivity.
• Health sciences librarians should not make use of university rankings materials lacking strong methodological foundations.
• This study''s bibliometric data may provide a starting point or point of comparison for future assessments.