最大化组织科学的影响:学科与学术领域交叉处的理论构建

学科与学术领域的交叉处为创造性的理论构建提供了重要机会。本文中,我们提出了在学科交叉处构建理论的3种模式,并强调了这3种模式的优势与不足。我们运用"影响轮(impact wheel)"把3种模式相互联系起来,直观地描述了它们对理论、学术领域、学科、研究者和外部相关者等五大范围的影响。尽管3种模式对这些方面的影响不尽相同,但当在学科交叉处的理论建构可以修订现有学科和学术领域边界,并产生新的学科和学术领域时,其影响最大。这样的理论建构并不常见,并且需要研究者具有挖掘组织科学更多潜能的特定技巧。     

A marketing plan: like it or not, you already have one

A physician executive dives into the world of marketing and discovers that just coming up with a marketing plan for a group practice can be very pricey.     

尼泊尔共产党（毛主义）的前世今生

尼泊尔的经验表明，单靠军事力量的强大无法保证能够取得反叛乱战争的胜利，人民的支持乃是决定性的因素。美国要想取得反叛乱战争的胜利，就必须加大对冲突国社会、经济．政治和文化背景的认识和了解，并对过去的反叛乱斗争策略做出深刻检讨。     

Immigrant incorporation in the garment industry of Los Angeles

This study expands immigrant social network theory and examined employment patterns in the garment industry in Los Angeles, California, among Latino workers employed by Asian immigrant entrepreneurs. The study determined that a large percentage of immigrant employees found their jobs through the immigrant economy. Entrepreneurship increased the supply of local jobs and expanded the economy at destination at no expense to natives. Immigrant entrepreneurs bought firms from nonimmigrant owners or started new ones with an immigrant labor supply. Massey's index is flawed due to its exclusion of the role of entrepreneurs. Migration networks facilitate entrepreneurship, but some ethnic groups have fewer entrepreneurs, such as Mexicans and Central Americans. A 1993 Los Angeles survey identified 3642 garment factories in its county. Mean employment was 27.1 persons. The garment industry was the 4th largest industry in the area in 1996, with 98,700 employees. It represented 6% of all wage and salary employees in the City and 5.5% of the immigrant labor force in the County in 1990. 93% of garment workers in 1990 were immigrants. It is estimated that 51% of garment factory owners were Asians; most employees were Latinos. Census figures on sewing machine operators indicated 47.3% of owners were Whites and 42.45 were Asians. 53.3% of employees were other ethnic groups, 14.5% were Asians, and 32.2% were Whites. It is estimated that 47.2% of total employment was due to the immigration economy. 71.5% of the total employment in the garment industry was in the immigrant sector.     

The industrial division of labor among immigrants and internal migrants to the Los Angeles economy

This study examined the industrial division of labor among immigrants and in-migrants in the Los Angeles, California, metropolitan area. It addresses debates about channeling of new arrivals into jobs among similar ethnic groups and human capital views. Data were obtained from the 1990 Census on resident native-born, resident foreign-born, in-migrants, and recent immigrants who arrived during 1985-90. Light and Rosenstein's (1995) concepts of groups and their resources were used to organize ideas about ethnic networks and their effectiveness in channeling migrant workers into 15 industrial sectors. Sectoral differences were revealed with the familiarity index of dissimilarity. Findings reveal that social networks were the strongest for Koreans, who supplied work for recent arrivals in the same sectors as Korean-born residents, regardless of education. Mexican new arrivals were less likely to work in the same sectors as their resident Mexican counterparts. Mexican networks placed new arrivals in durable manufacturing in the 1960s and 1970s when it was a key source of employment. By the 1980s and 1990s, the economy shifted and employment went down in durable manufacturing. Mexicans thus found employment elsewhere. Native White and Black in-migrants had the strongest channeling into same sector jobs. This is attributed to the small streams, the ability of the labor market to absorb these workers, and the availability of job vacancies among native out-migrants. Filipino migrants had similar patterns as Whites and Blacks. Mexican and Central American residents had more inter-ethnic competition over jobs than Whites or Blacks.     

Exposure of medical students to body fluids

Three hundred forty-two students at 3 Florida medical schools were surveyed concerning occupational exposures to blood and body fluids during their 3rd-year clerkship. The 16-item questionnaire was anonymously returned by 150 students, and differences among groups were assessed at p < .05. Most of the students complied with universal precautions guidelines (UVPG); 62 reported 101 exposures, including 9 with HIV-positive blood and body fluids. Most of the exposed students knew about the guidelines but regarded the incidents as irrelevant to their safety or supervision training. Noncompliant students reported significantly more exposures than compliant students. Time constraints, inconvenience of using gloves during procedures, and belief that patients were at low HIV risk discouraged adherence to the guidelines. Common practices following exposure were "no action" or "washed area only" without medical follow-up. Medical students' UVPG adherence should be increased by workload modification, user-friendly safety products, and supervised practice training in clinical exposure settings.     

Prevalence of alcohol-use disorders and alcohol-related problems in a college student sample

Most studies of alcohol consumption patterns and alcohol-related problems among college students have failed to include a diagnostic measure based on Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria. Applying the DSM-IV standards would facilitate an analysis of the prevalence of alcohol-use disorders and individual symptoms of those disorders. A structured diagnostic interview based on DSM-IV criteria (the alcohol section of the Substance Abuse Module) and several alcohol screening instruments were administered to 306 undergraduate students at an urban commuter campus. The prevalence of current and lifetime alcohol-use disorders, individual symptoms of those disorders, and other alcohol-related problems are reported, as well as data regarding alcohol consumption patterns and binge drinking. The data are analyzed in terms of demographic variables, including sex, ethnicity, year in school, age, and marital status of those in the sample.