A Comparison and Decomposition of Reform-Era Labor

A comparison and decomposition

of reform-era labor force participation rates of China’s ethnic minorities and Han majority

Margaret Maurer-Fazio and James W.Hughes

Department of Economics,Bates College,Lewiston,Maine,USA,and

Dandan Zhang

Research School of Social Sciences,Australian National University,

Canberra,Australia

Abstract

Purpose –The purpose of the paper is to examine observed differences in China’s ethnic majority and minority patterns of labor force participation and to decompose these differences into treatment and endowment effects.

Design/methodology/approach –Data from the three most recent population censuses of China are employed to explore differences in the labor force participation rates of a number of China’s important ethnic groups.Gender-separated urban labor force participation rates are estimated using logit regressions,controlling for educational attainment,marital status,pre-school and school-age children,household size,age,and measures of local economic conditions.The focus is on the experience of six minority groups (Hui,Koreans,Manchu,Mongolians,Uygurs,and Zhuang)in comparison to the majority Han.The technique developed by Borooah and Iyer is adopted to decompose the differences in labor force participation rates between pairs of ethnic groups into treatment and endowment effects.

Findings –Sizeable differences are found between the labor force participation rates of prime-age urban women of particular ethnic groups and the majority Han.Men’s participation rates are very high (above 95percent)and exhibit little difference between Han and ethnic minorities.For almost all pairwise comparisons between Han and ethnic women,it is found that differences in coef?cients account for more than 100percent of the Han-ethnic difference in labor force participation.Differences in endowments often have substantial effects in reducing this positive Han margin in labor force participation.Roughly speaking,treatment of women’s characteristics,whether in the market or socially,tend to increase the Han advantage in labor force participation.The levels of these characteristics on average tend to reduce this Han advantage.

Research limitations/implications –The paper analyses only one aspect of the economic status of China’s ethnic minorities –labor force participation.It would be useful also to examine income,educational attainment,occupational attainment,and unemployment.

Originality/value –This paper contributes to and expands the scant literature on ethnicity in China’s economic transition.

Keywords Ethnic minorities,Labour,Economic reform,Employee participation,China Paper type Research paper

All nationalities in the People’s Republic of China are equal.[...]Discrimination against and oppression of any nationality are prohibited (Article 4of the Constitution of the People’s Republic of China).

The current issue and full text archive of this journal is available at https://www.wendangku.net/doc/0b19029159.html,/0143-7720.htm

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International Journal of Manpower Vol.31No.2,2010pp.138-162

q Emerald Group Publishing Limited 0143-7720

DOI 10.1108/01437721011042241

1.Introduction

This paper contributes to the scant literature on ethnicity in China’s economic transition.In the late1970s the Chinese leadership embarked on a program of economic reform that initiated a transition to a market economy.At the national level,the transition led to rapid and sustained income growth and welfare improvements.Less is known about how China’s different ethnic groups have fared in the reform process.The aim of this paper is to?ll part of the gap.

2.China’s ethnic minorities

According to China’s2000population census,8.5percent of the Chinese population (106million people)was classi?ed as ethnic minority.When we use the terms“ethnic minority”,“national minority”or“minority people”here,we are referring to the55 national minorities that,with the Han majority,make up the56ethnic groups of?cially recognized by the Chinese central government.Chinese policies towards ethnic minorities stem in part from a legacy inherited from dynastic leaders,in part from an ethnic identi?cation project built on Stalinist principles and implemented in the early years of the People’s Republic,and in part from an array of adaptations to speci?c local situations.In the mid-1980s,government policy increased the bene?ts to minority identi?cation[1]and thus provided an incentive for change in ethnic identity. Consequently,when on the basis of fertility trends an increase of ten million was expected,the actual number of people self-identifying as ethnic minorities in the1990 census increased by24million[2].

Much of China’s total land area(63.9percent),particularly the politically sensitive border regions in Northwestern,Southwestern,and Northeastern China,is designated as autonomous ethnic minority regions(State Ethnic Affairs Committee,2003,p.545), and many of China’s minority people(75percent)reside in these specially designated areas(Information Of?ce of the State Council of the People’s Republic of China,1999, p.15).Published economic statistical data on China’s minority peoples is almost always presented by autonomous region rather than by ethnic group[3].This makes it dif?cult to shed light on questions about the economic well-being of China’s minority peoples since the Han often comprise a signi?cant proportion of the population in autonomous regions[4].

Overall economic indicators show a rising standard of living in ethnic minority regions.Colin Mackerras(2003,pp.56-76)examines numerous indicators of the standard of living in China’s minority areas,including measure of rural income,wages, healthcare provision,infrastructure development,and industrial development, concluding that since1990minorities have radically improved their standard of living.However,these improvements have not kept pace with developments in the national economy.China’s minorities dwell predominately in western China,a region that includes China’s poorest provinces and lags far behind the Eastern seaboard provinces in terms of income and economic development.

Socioeconomic treatises on China’s ethnic groups(as opposed to autonomous regions)are rare.One notable exception is the work of Gustafsson and Li(1998,2003), who make an important contribution to the economic literature about China’s minority nationalities.They employ survey data gathered in1988and1995from19provinces, to assess the differences in rural income between the Han majority and ethnic minorities(grouped together).They?nd that the per capita income gap of19.2percent

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139

in the earlier period grew to 35.9percent in the latter period.When they decompose the income differential into differences due to endowments and treatment they ?nd that the lion’s share of the differential is due to differences in endowments and that minority incomes are lower than Han incomes largely due to location.They note that China’s minorities are clustered in provinces with low per capita GDP and tend to dwell in mountainous areas and areas of?cially designated as poor.

Gustaffson and Ding (2008)build on this earlier work,employing survey data from 22provinces gathered in 2002to analyze differences between ethnic minority people (grouped together)and majority people in the levels of temporary and persistent poverty in rural China.They too argue that poverty in rural China has a very strong spatial dimension –that ethnic minorities have higher rates of both persistent and temporary poverty because minorities are concentrated in Western China,home to most of China’s poor.They ?nd that the rates of poverty differ little between minorities and the majority in Western China.They report that factors such as the education level of the household head,village mean income,and whether the village is located in a mountainous area are much more important than ethnicity in explaining poverty,and that ethnic minority status has little independent effect.

Hannum and Xie (1998),in another important contribution to this literature,focus on an array of particular minorities in a single province.They employ population census data to examine the effects of market reform on differences in occupational attainment of Xinjiang’s (mainly Turkic)minorities in comparison to the Han.Hannum and Xie (1998)?nd that the ethnic gap in occupational attainment between the Han and the minorities widened between the 1982and 1990censuses.They attribute the rising gap to an increased gap in educational attainment between the Han and the minorities and a strengthening of the relationship between educational attainment and higher-status occupations.

Ding and Li (2009)analyze income inequality and differences in income determination for Hui and Han urban residents in Ningxia based on survey data gathered in 2007.They decompose differences in earnings into treatment and endowment effects and ?nd that the treatment effects are more important than endowment effects in explaining the incomes differences between the Hui and Han.It is important to note,however,that the treatment effects do not necessarily favor the Han.Ding and Li (2009)report that returns to education are somewhat higher for the Han than the Hui,while the returns to experience are higher for the Hui than the Han.Similarly,party membership favors (has a bigger return for)the Hui while state ownership of the workplace favors the Han.Maurer-Fazio et al.(2007)analyze trends in the labor force participation of China’s minorities between 1990and 2000.They ?nd that minorities were affected more adversely than Han by reductions in urban sector employment and exited the labor force more rapidly than Han.

The papers of Gustafsson and Li (1998,2003)and Hannum and Xie (1998)suggest that minorities have not fared well in China’s transition –that both rural income and occupational attainment gaps between minorities and the Han have widened.The former paper argues that location rather than ethnicity is the causal factor in the widening rural income gap while the latter paper suggests that important ethnic differences in labor market outcomes remain even after carefully controlling for location.Similarly,Gustaffson and Ding (2008)argue that rural poverty is better

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explained by location rather than ethnicity,while Ding and Li(2009)?nd ethnicity a signi?cant factor in urban income determination.

This nascent but growing literature on ethnicity in China’s transition has addressed rural and urban income,rural poverty,and occupational attainment and touched on urban labor force participation.We add to this literature by deepening the analysis of the labor force participation of a number of China’s important ethnic groups.We expand on the earlier analysis of Maurer-Fazio et al.(2007)in several signi?cant ways.First,we extend the time period from1982to2000and include a larger set of ethnic minorities.More importantly,we control for both demographic factors and local economic conditions.We are particularly interested in whether the differences in majority and minority economic labor force participation rates are mainly attributable to differences in ethnic groups’attributes or the treatment of those attributes.

3.Research strategy

We utilize the method developed by Borooah and Iyer(2005)to decompose differences in labor force participation rates between the Han majority and a number of minorities into coef?cient and attribute effects.The Borooah-Iyer model extends the well-known Oaxaca-Blinder decomposition method to logit models and,importantly for our case, allows the inclusion of multiple groups.Our analysis is based on the data of the1982, 1990,and2000population censuses of China,which identify individuals’ethnic status and allow us to overcome some of the above-mentioned data scarcity problems.

We focus our analysis on the labor force participation patterns of urban residents[5]. We concentrate on six important minority groups and the Han majority.The limited number of urban ethnic minority residents in the census samples determined which groups we could include in our analysis.We’ve included every minority group with suf?cient sample size to successfully run(with a consistent set of explanatory variables)the logits which underlie the Borooah-Iyer method.We thus carry out pair wise comparisons of the differences in labor force participation between the Han and Hui,Koreans,Manchu,Mongolians,Uygurs,and Zhuang[6].

We divide our samples by gender and separately analyze men’s and women’s labor force participation.Men’s labor force participation rates for both majority and minority men are extremely high in international perspective.There is very little difference by ethnicity between men’s labor force participation rates,as can be seen in Tables I-IV. Therefore,in the following sections of this paper,we focus our analysis and discussion on the differences in women’s labor force participation.

In the next section we discuss our theoretical predictions about how the reforms might in?uence labor force participation rates.The following section describes the data used in this project.We then report estimates of urban labor force participation rates using logit regressions on the1982,1990,and2000data.These regressions controls for ethnic group,educational attainment,marital status,household composition,age,and local economic conditions and allow us to determine whether the participation rates of particular ethnic groups differ from that of the Han majority and whether there are any discernible trends in such differences over time.We then employ the Borooah Iyer technique to decompose the differences in labor force participation into treatment/coef?cient and attribute/endowment effect.We summarize our?ndings in the?nal section of the paper.

Labor force participation

rates

141

V a r i a b l e

H a n H u i K o r e a n M a n c h u M o n g o l i a n U y g u r

Z h u a n g

L a b o r f o r c e p a r t i c i p a t i o n r a t e

0.988

0.9830.9800.9890.989

0.988

0.976

E d u c a t i o n l e v e l ,p r o p o r t i o n w i t h ...P r i m a r y o r l e s s 0.3590.3470.1180.2740.3580.5870.478J u n i o r m i d d l e s c h o o l 0.4050.4320.4550.4420.3190.2590.335S e n i o r m i d d l e s c h o o l 0.1720.1650.3110.2130.2230.1210.132P o s t -s e c o n d a r y

0.064

0.0560.1160.0710.100

0.034

0.055

M a r i t a l s t a t u s ,p r o p o r t i o n N o t m a r r i e d 0.1290.1180.0750.0840.0870.1300.114M a r r i e d ,s p o u s e n o t p r e s e n t

0.105

0.0970.0710.074

0.046

0.110

0.066

H o u s e h o l d c o m p o s i t i o n ,m e a n N u m b e r o f a d u l t s (a g e d 18t)2.7862.7932.8562.8512.7202.5852.925N u m b e r o f c h i l d r e n a g e d 0-50.3900.4090.4250.4040.4970.7700.775N u m b e r o f c h i l d r e n a g e d 6-120.5820.5940.5900.6060.6990.8810.844N u m b e r o f c h i l d r e n a g e d 13-17

0.242

0.2440.273

0.251

0.260

0.262

0.277

A g e :p r o p o r t i o n i n e a c h c a t e g o r y 25-290.2840.2710.2760.2810.2710.2550.28130-340.2130.2200.2370.2080.1910.2110.22935-390.1520.1500.1360.1540.1570.1700.12140-440.1540.1740.1670.1600.1850.1660.16645-50

0.198

0.1850.183

0.197

0.196

0.197

0.202

P r e f e c t u r a l u n e m p l o y m e n t r a t e s (p e r c e n t )

1.58

1.67

2.46

2.29

1.98

1.15

2.74

N u m b e r o f o b s e r v a t i o n s

218,8462,984

785

1,515

439

745

668

N o t e :D a t a s o u r c e s f o r a l l t a b l e s a r e a 1p e r c e n t m i c r o -s a m p l e s o f t h e P o p u l a t i o n C e n s u s e s o f C h i n a f o r t h e y e a r s 1982a n d 1990,a n d 0.095p e r c e n t m i c r o -s a m p l e o f t h e P o p u l a t i o n C e n s u s o f C h i n a 2000

Table I.

Sample statistics:urban men aged 25-50in 1982

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V a r i a b l e

H a n H u i K o r e a n M a n c h u M o n g o l i a n U y g u r Z h u a n g

L a b o r f o r c e p a r t i c i p a t i o n r a t e

0.991

0.9870.9830.9920.9820.9670.991

E d u c a t i o n l e v e l ,p r o p o r t i o n w i t h ...P r i m a r y o r l e s s 0.2520.2420.0940.2480.1820.3780.409J u n i o r m i d d l e s c h o o l 0.4040.4490.4280.4300.3560.2860.370S e n i o r m i d d l e s c h o o l 0.2610.2470.3750.2480.3470.2280.192P o s t -s e c o n d a r y

0.083

0.0620.1030.0740.1160.107

0.030

M a r i t a l s t a t u s ,p r o p o r t i o n N o t m a r r i e d 0.0900.0810.1010.0810.0650.1470.107M a r r i e d ,s p o u s e n o t p r e s e n t

0.051

0.0560.0190.0290.0280.081

0.032

H o u s e h o l d c o m p o s t i o n ,m e a n N u m b e r o f a d u l t s (a g e d 18t)2.6042.5992.6622.5952.5922.5562.976N u m b e r o f c h i l d r e n a g e d 0-50.4070.4370.4190.4300.5980.8020.666N u m b e r o f c h i l d r e n a g e d 6-120.4920.5170.4790.5220.6780.7290.850N u m b e r o f c h i l d r e n a g e d 13-17

0.207

0.2060.2030.1980.171

0.216

0.245

A g e ,p r o p o r t i o n i n e a c h c a t e g o r y 25-290.2510.2490.2290.2630.3130.2750.28030-340.2280.2240.2750.2660.2730.2300.19335-390.2220.2200.2270.2190.2150.1740.21140-440.1590.1620.1390.1310.1010.1710.17045-50

0.141

0.1450.1300.121

0.099

0.150

0.147

P r e f e c t u r a l u n e m p l o y m e n t r a t e s (p e r c e n t )

1.27

1.60

2.32

1.56

1.02

2.49

1.08

N u m b e r o f o b s e r v a t i o n s

282,7202,975841

3408

1298

1296

2,996

Table II.

Sample statistics:urban men aged 25-50in 1990

Labor force participation

rates

143

V a r i a b l e

H a n H u i K o r e a n M a n c h u M o n g o l i a n U y g u r

Z h u a n g

L a b o r f o r c e p a r t i c i p a t i o n r a t e

0.962

0.9430.8790.9610.951

0.928

0.971

E d u c a t i o n l e v e l ,p r o p o r t i o n w i t h ...P r i m a r y o r l e s s 0.1370.1790.0300.1260.0650.2570.168J u n i o r m i d d l e s c h o o l 0.4410.4470.3580.4600.3220.3290.405S e n i o r m i d d l e s c h o o l 0.2710.2400.4570.2430.3710.2710.269P o s t -s e c o n d a r y

0.150

0.1340.1550.1710.241

0.144

0.158

M a r i t a l s t a t u s ,p r o p o r t i o n N o t m a r r i e d 0.0900.1060.1850.0830.0700.1160.122M a r r i e d ,s p o u s e n o t p r e s e n t

0.053

0.0570.0520.031

0.022

0.021

0.073

H o u s e h o l d c o m p o s i t i o n ,m e a n N u m b e r o f a d u l t s (a g e d 18t)2.5012.5252.5262.5052.3772.5892.516N u m b e r o f c h i l d r e n a g e d 0-50.2260.2500.1250.1990.2060.4590.281N u m b e r o f c h i l d r e n a g e d 6-120.3890.4180.3060.3510.4800.6030.394N u m b e r o f c h i l d r e n a g e d 13-17

0.206

0.2160.237

0.261

0.201

0.199

0.213

A g e :p r o p o r t i o n i n e a c h c a t e g o r y 25-290.1980.2090.1510.1680.2380.2500.22730-340.2260.2190.2110.2420.2110.2570.25535-390.2150.2010.2590.2170.2170.2290.19840-440.1730.1540.2240.1820.1920.1510.15545-50

0.188

0.217

0.155

0.191

0.141

0.113

0.165

P r e f e c t u r a l u n e m p l o y m e n t r a t e s (p e r c e n t )

4.79

4.64

9.65

8.25

5.59

3.88

3.24

N u m b e r o f o b s e r v a t i o n s

87,393

912

232

828

369

292

647

Table III.

Sample statistics:urban men aged 25-50in 2000

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L F P r a t e d i f f e r e n c e s

C o e f ?c i e n t s e f f e c t C o e f ?c i e n t p e r c e n t a g e E n d o w m e n t e f f e c t E n d o w m e n t p e r c e n t a g e

1982H a n -H u i 0.00510.0065126.5620.0014226.56H a n -K o r e a n 0.00810.0137169.2920.0056269.29H a n -M a n c h u 20.00110.00212189.5420.0032289.54H a n -M o n g o l i a n 20.00090.0006262.8620.0015162.86H a n -U y g u r 20.00020.041321,8011.4320.041618,111.43H a n -Z h u a n g

0.0116

0.008068.620.003731.38

1990H a n -H u i 0.00380.003797.220.00012.78H a n -K o r e a n 0.00760.001317.680.006382.32H a n -M a n c h u 20.001120.000980.2220.000219.78H a n -M o n g o l i a n 0.00870.0140161.0220.0053261.02H a n -U y g u r 0.02410.0253105.0120.001225.01H a n -Z h u a n g

0.0003

0.0008264.3320.0005

2164.33

2000H a n -H u i 0.01860.016388.040.002211.96H a n -K o r e a n 0.08220.1122136.3720.0299236.37H a n -M a n c h u 0.000220.005422,720.870.00572,820.87H a n -M o n g o l i a n 0.01030.004341.780.006058.22H a n -U y g u r 0.03350.1039310.4620.07042210.46H a n -Z h u a n g

20.009120.005460.0220.0036

39.98

N o t e s :1982:l o g i t f o r M o n g o l i a n f a i l s x 2t e s t .2000:l o g i t s f o r Z h u a n g a n d K o r e a n s f a i l x 2t e s t s

Table IV.Decomposition of differences in Chinese

men’s labor force

participation rates:urban

men aged 25-50

Labor force participation

rates

145

https://www.wendangku.net/doc/0b19029159.html,bor force participation rates

China’s economic reforms have widened the range of women’s opportunities for paid employment as the economic structure shifted away from capital-intensive heavy industry towards labor-intensive light industry and commercial services.Economic growth and concomitant wage increases raise the opportunity cost of not working.On this basis,we would expect to see higher levels of labor force participation in 1990and 2000than in 1982,as the gains from such participation increase.China,however,has long had very high labor force participation rates by international standards,especially for women.The labor force participation rates of urban women in 1982(very early in the reform period)were 87.5for women aged 25-50and 70.5for women aged 15and above[7].Thus,economic growth may not draw signi?cant numbers of new workers into the labor force,as not many adults were outside the labor force in the pre-reform period.

The transition also created new obstacles for women’s labor force participation.The state’s retreat from its commitment to socialist ideology and enforcement of workplace protections for women coincided with a re-emergence of traditional patriarchal values (Croll,1995;Entwisle and Henderson,2000).This retreat combined with growing pressure to reduce the size of the state-owned enterprise work force put pressure on women,especially older women,to leave the labor force and return to more subordinate roles.In many cases,the effort expenditure required at the workplace increased with reform-era changes in workplace discipline,making it more dif?cult for working women to cope with household responsibilities and thus raising the costs of labor force participation,particularly for married women with young children.We thus add variables to control for the number of children of various age groups.

At the household level,rising incomes of spouses and/or other household members can be viewed as an income effect for married women that would allow some individuals to withdraw from the labor force when their spouse’s earnings met household income https://www.wendangku.net/doc/0b19029159.html,bor force participation of married women could decline as a result of this phenomenon.Such a trend,however,might be dampened by China’s birth planning policies,implemented ?rst as the wan xi shao policy (later births,longer intervals,fewer children)in 1971and followed by the even more stringent “one-child”policy of 1979,which drastically reduced total fertility rates and affected the value of time spent in home production.The vast majority of Chinese women continue to marry and to raise children but they have far fewer children and are ?nished with childbearing and childrearing at earlier ages than their mothers and grandmothers.

Education is increasingly rewarded in the Chinese workplace (Maurer-Fazio,1999,Zhang et al.,2005).We thus expect to observe a positive relationship between level of education and labor force participation.

The restructuring of the state-owned sector in the latter half of the 1990s led to the laying off of many millions of urban workers.Extended periods of lay-off led,in turn,to withdrawal from the labor force of some of these workers –the discouraged worker effect.The layoffs appeared to fall disproportionately on women and older workers (Giles et al.,2006;Maurer-Fazio,2006).We enter a series of age dummies to allow for changing age effects.

Finally,and importantly for the focus of this paper,with a relaxation of the protections afforded workers in the socialist period,managers may have begun to

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indulge prejudices against particular ethnic groups by refusing to hire or disproportionately laying off members of these groups.If such practices are widespread,members of disadvantaged groups could become“discouraged workers”and withdraw from the labor force.

5.Data description

The data employed in this project are drawn from the three most recent population censuses of China.Our analysis is based on1percent micro data samples of the1982 and1990censuses and a0.095percent micro data sample of the2000census[8].We use all the data for urban residents available in the1982and2000census micro samples and take a random50percent sub-sample of the urban residents in the1990micro sample.

Individuals are considered to be in the labor force if they had a job on the day of the census or if they were unemployed and looking for work at that time.We equate those classi?ed as“waiting for work”in the earlier censuses as seeking employment and thus part of the labor force.

Ethnicity is reported directly on the census questionnaires.The number of ethnic groups is consistent across all three censuses.We restrict the ages of the individuals included in our analysis to those between25and50.The lower age bound allows us to focus our analysis on those who have completed their schooling.The upper bound is prescribed by two factors.First,and importantly,the Chinese population census data reports household relationships relative to the household head.This makes it very dif?cult to accurately assign dependent children to parents in multi-generation, extended households.To reliably sort out which children belong to which adults in the census households we make use of a set of questions related to fertility that is asked only of women aged15to50[9].Secondly,women who are considered“ordinary”workers face a retirement age of50.

For each person in our census samples,we have created a set of variables that characterize ethnicity,the number of adults in the household,the age distribution of children in the household,marital status[10],education[11],and age.

We also created a set of variables at the prefecture and provincial levels that capture local economic conditions–provincial per capital urban income,provincial real GDP growth rates over the previous?ve years,and prefectural unemployment rates[12]. These variables are intended to capture differences in labor market opportunities and the general health of the local economy[13].

6.Results and discussion

We?rst estimate logits on labor force participation for1982,1990,and2000with controls for ethnic group,educational attainment,marital status,household composition,age,and local economic conditions.The results are presented in Tables V-VII.The base case consists of married Han of age category25-29with junior middle-school education.All explanatory variables are highly signi?cant save for one or two ethnic group indicators in particular years.

Focusing?rst on the ethnic group indicators,we see that while in1982and1990Hui and Korean women had labor force participation rates that were indistinguishable from the Han,this changes over the course of the reforms.By2000,Hui and Korean women,respectively,were3.5and5.5percent less likely to participate in the labor force

Labor force participation

rates

147

V a r i a b l e s

C o e f ?c i e n t R o b u s t s t a n d a r d e r r o r Z v a l u e s M a r g i n a l p r o b a b i l i t y d y /d x

X -b a r

E t h n i c g r o u p H u i 0.0490.0560.8800.0040.013K o r e a n 0.1920.1091.7700.0150.004M a n c h u 20.4420.08125.48020.0430.005M o n g o l i a n 20.8040.12326.55020.0910.002U y g u r 21.4870.094215.85020.2140.003Z h u a n g 1.7930.15911.2800.0740.003O t h e r e t h n i c m i n o r i t i e s

1.171

0.1259.370

0.061

0.005

E d u c a t i o n a l a t t a i n m e n t P r i m a r y s c h o o l o r l e s s 20.771

0.016248.740

20.077

0.199

B a s e c a s e :j u n i o r m i d d l e s c h o o l S e n i o r m i d d l e s c h o o l 1.3090.03438.2300.0750.139P o s t -s e c o n d a r y e d u c a t i o n

1.318

0.07018.890

0.066

0.029

M a r i t a l s t a t u s N o t m a r r i e d 20.058

0.031

21.920

20.005

0.066

B a s e c a s e :m a r r i e d s p o u s e p r e s e n t M a r r i e d s p o u s e e l s e w h e r e

20.183

0.019

29.450

20.016

0.166

H o u s e h o l d c o m p o s i t i o n N u m b e r o f a d u l t s (a g e d 18a n d o v e r )20.0870.006215.30020.0072.759N u m b e r o f c h i l d r e n a g e d 0-520.4700.014233.28020.0390.421N u m b e r o f c h i l d r e n a g e d 6-1220.1460.009216.16020.0120.678N u m b e r o f c h i l d r e n a g e d 13-17

0.063

0.017

3.800

0.005

0.305

(c o n t i n u e d )

Table V.

Labor force participation of Chinese urban women,aged 25-50,in 1982:logistic regressions and marginal effects

IJM 31,2

148

V a r i a b l e s C o e f ?c i e n t R o b u s t s t a n d a r d e r r o r Z v a l u e s M a r g i n a l p r o b a b i l i t y d y /d x X -b a r

A g e c a t e g o r y

B a s e c a s e :a g e d 25-29A g e d 30-340.0920.0233.9400.0070.216A g e d 35-3920.2150.02927.53020.0190.160A g e d 40-4420.6140.028222.23020.0600.161A g e d 45-50

21.762

0.025271.17020.228

0.181

E c o n o m i c e n v i r o n m e n t P r e f e c t u r a l u n e m p l o y m e n t r a t e 20.2210.006238.49020.0181.577P r o v i n c i a l r e a l p e r c a p i t a i n c o m e 0.1120.00335.3500.00910.168P r o v i n c i a l r e a l ?v e -y e a r G D P g r o w t h

0.123

0.00428.0300.010

9.158

C o n s t a n t

1.3070.06021.650

S u m m a r y s t a t i s t i c s M e a n L F P 0.873P r e d i c t e d L F P 0.910

L o g p s e u d o l i k e l i h o o d 279,611.705N u m b e r o f o b s e r v a t i o n s 245,402W a l d x 2(23)23,942P r o b .x 2

0.000P s e u d o R 2

0.149

Table V.

Labor force participation

rates

149

V a r i a b l e s

C o e f ?c i e n t R o b u s t s t a n d a r d e r r o r Z v a l u e s M a r g i n a l p r o b a b i l i t y d y /d x

X -b a r

E t h n i c g r o u p H u i 0.0950.0561.7100.0080.010K o r e a n 20.0840.09820.85020.0080.003M a n c h u 20.6830.045215.19020.0800.010M o n g o l i a n 21.0960.065216.81020.1500.005U y g u r 20.9650.066214.53020.1260.004Z h u a n g 1.5350.08917.1800.0790.011O t h e r e t h n i c m i n o r i t i e s

20.034

0.04720.730

20.003

0.015

E d u c a t i o n a l a t t a i n m e n t P r i m a r y s c h o o l o r l e s s 20.546

0.015235.780

20.059

0.115

B a s e c a s e :j u n i o r m i d d l e s c h o o l S e n i o r m i d d l e s c h o o l 1.2760.02064.1500.0910.236P o s t -s e c o n d a r y e d u c a t i o n

2.653

0.08132.580

0.102

0.040

M a r i t a l s t a t u s N o t m a r r i e d 0.133

0.031

4.220

0.011

0.042

B a s e c a s e :m a r r i e d s p o u s e p r e s e n t M a r r i e d s p o u s e e l s e w h e r e

20.025

0.022

21.130

20.002

0.085

H o u s e h o l d c o m p o s i t i o n N u m b e r o f a d u l t s (a g e 18a n d o v e r )20.0400.00527.29020.0042.620N u m b e r o f c h i l d r e n a g e d 0-520.4100.011237.55020.0370.405N u m b e r o f c h i l d r e n a g e d 6-1220.2350.010224.46020.0210.534N u m b e r o f c h i l d r e n a g e d 13-17

20.143

0.015

29.720

20.013

0.249

(c o n t i n u e d )

Table VI.

Labor force participation of Chinese urban women,age 25-50in 1990:logistic regressions and marginal effects

IJM 31,2

150

V a r i a b l e s C o e f ?c i e n t R o b u s t s t a n d a r d e r r o r Z v a l u e s M a r g i n a l p r o b a b i l i t y d y /d x X -b a r

A g e c a t e g o r y

B a s e c a s e :a g e 25-29A g e d 30-340.1740.0208.6100.0150.224A g e d 35-390.1530.0226.9100.0130.222A g e d 40-4420.3200.024213.55020.0320.155A g e d 45-50

21.295

0.022258.88020.169

0.140

E c o n o m i c e n v i r o n m e n t P r e f e c t u r a l u n e m p l o y m e n t r a t e 20.2500.004265.03020.0231.269P r o v i n c i a l r e a l p e r c a p i t a i n c o m e 0.0150.00034.4800.00155.606P r o v i n c i a l r e a l ?v e -y e a r G D P g r o w t h

20.067

0.004216.65020.006

5.956

C o n s t a n t

2.3090.04057.690

S u m m a r y s t a t i s t i c s M e a n L F P 0.864P r e d i c t e d L F P 0.899

L o g p s e u d o l i k e l i h o o d 216,561.750N u m b e r o f o b s e r v a t i o n s 303,694W a l d x 2(23)22,900P r o b .x 2

0.000P s e u d o R 2

0.120

Table VI.

Labor force participation

rates

151

V a r i a b l e s

C o e f ?c i e n t R o b u s t s t a n d a r d e r r o r Z v a l u e s M a r g i n a l p r o b a b i l i t y d y /d x

X -b a r

E t h n i c g r o u p H u i 20.2000.07822.56020.0350.010K o r e a n 20.3040.15321.98020.0550.003M a n c h u 0.0010.0830.0100.0000.009M o n g o l i a n 20.3160.11422.77020.0570.005U y g u r 20.6190.12225.08020.1200.004Z h u a n g 0.5630.1095.1600.0790.007O t h e r e t h n i c m i n o r i t i e s

0.176

0.0712.460

0.028

0.015

E d u c a t i o n a l a t t a i n m e n t P r i m a r y s c h o o l o r l e s s 20.216

0.04025.390

20.038

0.034

B a s e c a s e :j u n i o r m i d d l e s c h o o l S e n i o r m i d d l e s c h o o l 0.6640.02132.2800.1000.251P o s t -s e c o n d a r y e d u c a t i o n

2.193

0.05241.850

0.212

0.099

M a r i t a l s t a t u s N o t m a r r i e d 0.437

0.041

10.580

0.064

0.057

B a s e c a s e :m a r r i e d s p o u s e p r e s e n t M a r r i e d s p o u s e e l s e w h e r e

0.047

0.034

1.410

0.008

0.071

H o u s e h o l d c o m p o s i t i o n N u m b e r o f a d u l t s (a g e d 18a n d o v e r )0.0850.0099.3700.0142.510N u m b e r o f c h i l d r e n a g e d 0-520.3020.021214.16020.0500.225N u m b e r o f c h i l d r e n a g e d 6-1220.0430.01622.71020.0070.410N u m b e r o f c h i l d r e n a g e d 13-17

0.115

0.022

5.130

0.019

0.221

(c o n t i n u e d )

Table VII.

Labor force participation of Chinese urban women,aged 25-50in 2000:logistic regressions and marginal effects

IJM 31,2

152

V a r i a b l e s C o e f ?c i e n t R o b u s t s t a n d a r d e r r o r Z v a l u e s M a r g i n a l p r o b a b i l i t y d y /d x X -b a r

A g e c a t e g o r y

B a s e c a s e :a g e d 25-29A g e d 30-340.0800.0272.9000.0130.227A g e d 35-390.0620.0312.0000.0100.210A g e d 40-4420.2080.03226.48020.0360.166A g e d 45-50

20.955

0.029233.03020.184

0.184

E c o n o m i c e n v i r o n m e n t P r e f e c t u r a l u n e m p l o y m e n t r a t e 20.0680.002227.62020.0114.779P r o v i n c i a l r e a l p e r c a p i t a i n c o m e 0.0030.0007.1400.00165.563P r o v i n c i a l r e a l ?v e -y e a r G D P g r o w t h

0.068

0.0079.5000.011

9.057

C o n s t a n t

0.4310.0755.780

S u m m a r y s t a t i s t i c s M e a n L F P 0.762P r e d i c t e d L F P 0.790

L o g p s e u d o l i k e l i h o o d 247,140.171N u m b e r o f o b s e r v a t i o n s 93,145W a l d x 2(23)6,183P r o b .x 2

0.000P s e u d o R 2

0.077

Table VII.

Labor force participation

rates

153

than Han women (see column 4,“Marginal probabilities”in Tables V-VII)[14].The vast majority of Koreans live in Northeastern China,an area hit hard by the decline of inef?cient state-run enterprises.Korean men and women both exhibit steeper declines in participation rates than any other ethnic group studied here.

In 1982and 1990,Manchu,Mongolian,Uygur women were signi?cantly less likely to be in the labor force than Han women.By 2000,the Manchu women became indistinguishable from Han in terms of labor force participation.The very large gap between Uygur and Han participation in 1982(21.4percent)was reduced to 12.6percent by 1990and remained at 12percent through 2000.

The Zhuang are the only ethnic group with labor force participation rates substantially and signi?cantly higher than that of the Han.Throughout the whole period,Zhuang women’s participation rates remained 7.4-7.9percent above that of the Han.

As expected,education became an increasingly important determinant of labor force participation.At the beginning of the period,women with post-secondary educations were 6.6percent more likely to be in the labor force than those with junior middle-school educations.By the end of the period,those with post-secondary education were 21.2percent more likely to be in the labor force.Throughout the period,women with pre-school age children were consistently 4-5percent less likely to be in the labor force than others.

Women’s labor force participation is inversely related to local unemployment rates (suggesting a discouraged-worker effect)and,generally,positively related to the level of provincial urban income and provincial rates of GDP growth.The sample statistics presented in Tables VIII-X reveal a marked decline in urban women’s labor force participation between 1990and 2000which is not mirrored in the sample statistics for men (Tables I-III).

To better understand whether the differences between Han and ethnic minority participation rates are due to differences in their endowments (education level,marital status,household composition,age structure,and location)or to the coef?cients (responses to or treatment)of those attributes,we use the Borooah-Iyer decomposition technique.Its coef?cient effect is derived by estimating the participation rate that would arise if all the women in the sample were treated as Han and subtracting from this the participation rate that would arise if all women in the sample were treated as one of the ethnic groups –for example,Manchu.Borooah and Iyer (2005)refer to this as the difference in synthetic probabilities,or in our case,the difference in synthetic participation rates.The endowment effect is the difference in Han and Manchu participation rates resulting from Han-Manchu differences in attributes when evaluated with a common coef?cient vector.We estimate the endowment effect by subtracting the difference in Han and Manchu synthetic participation rates from the difference between the actual,observed Han and Manchu participation rates.

In the labor force participation setting,we interpret the coef?cient effect to measure the “return”,or “treatment”of women’s average characteristics.If all women had Han average attributes rather than,say Uygur attributes,how would the difference in labor force participation change?We note that this treatment of attributes could be market-based (e.g.different returns to education)or cultural (e.g.different attitudes towards market and home production).The attributes effect in our model is broader

IJM 31,2

154

V a r i a b l e

H a n H u i K o r e a n M a n c h u M o n g o l i a n U y g u r Z h u a n g

L a b o r f o r c e p a r t i c i p a t i o n r a t e

0.873

0.8780.8740.8030.7730.6660.937

E d u c a t i o n l e v e l ,p r o p o r t i o n w i t h ...P r i m a r y o r l e s s 0.5110.4720.2770.3780.4590.6370.693J u n i o r m i d d l e s c h o o l 0.3220.3700.4570.4040.2570.2270.181S e n i o r m i d d l e s c h o o l 0.1390.1320.2360.1830.2210.1160.112P o s t -s e c o n d a r y

0.029

0.0260.0300.0350.0630.019

0.015

M a r i t a l s t a t u s ,p r o p o r t i o n N o t m a r r i e d 0.0660.0730.0450.0710.0700.1230.063M a r r i e d ,s p o u s e n o t p r e s e n t

0.167

0.1350.1070.1360.1010.074

0.166

H o u s e h o l d c o m p o s i t i o n ,m e a n N u m b e r o f a d u l t s (a g e d 18t)2.7592.7722.8842.8292.6762.6452.821N u m b e r o f c h i l d r e n a g e d 0-50.4160.4230.4210.4190.4860.7500.830N u m b e r o f c h i l d r e n a g e d 6-120.6730.6960.6140.5870.7071.1140.973N u m b e r o f c h i l d r e n a g e d 13-17

0.305

0.2980.3220.2870.284

0.394

0.344

A g e :p r o p o r t i o n i n e a c h c a t e g o r y 25-290.2830.2660.3070.3090.3020.2650.30030-340.2160.2280.2030.1950.1940.1910.21635-390.1600.1750.1290.1370.1620.1860.14440-440.1600.1650.1680.1630.1820.1700.17245-50

0.181

0.1660.1930.196

0.160

0.188

0.168

P r e f e c t u r a l u n e m p l o y m e n t r a t e s (p e r c e n t )

1.57

1.67

2.44

2.25

2.02

1.11

2.84

N u m b e r o f o b s e r v a t i o n s

236,8853191876

1260

444

775

814

Table VIII.

Sample statistics:urban women aged 25-50in

1982

Labor force participation

rates

155

V a r i a b l e

H a n H u i K o r e a n M a n c h u M o n g o l i a n U y g u r

Z h u a n g

L a b o r f o r c e p a r t i c i p a t i o n r a t e

0.866

0.8580.8310.7700.706

0.587

0.957

E d u c a t i o n l e v e l ,p r o p o r t i o n w i t h ...P r i m a r y o r l e s s 0.3790.3230.1780.3510.3180.4650.656J u n i o r m i d d l e s c h o o l 0.3430.3930.4210.3460.3100.2540.224S e n i o r m i d d l e s c h o o l 0.2380.2430.3360.2540.3150.2320.114P o s t -s e c o n d a r y

0.040

0.0410.0650.0490.058

0.048

0.006

M a r i t a l s t a t u s ,p r o p o r t i o n N o t m a r r i e d 0.0400.0550.0620.0350.0400.1340.060M a r r i e d ,s p o u s e n o t p r e s e n t

0.086

0.0870.0330.044

0.042

0.070

0.073

H o u s e h o l d c o m p o s i t i o n ,m e a n N u m b e r o f a d u l t s (a g e d 18t)2.6122.6152.6262.5852.6792.6532.942N u m b e r o f c h i l d r e n a g e d 0-50.3950.4210.4080.4620.5970.7800.655N u m b e r o f c h i l d r e n a g e d 6-120.5240.5270.4790.5470.6680.9050.927N u m b e r o f c h i l d r e n a g e d 13-17

0.248

0.2430.227

0.212

0.212

0.334

0.292

A g e :p r o p o r t i o n i n e a c h c a t e g o r y 25-290.2580.2550.2620.3050.3440.2750.28230-340.2240.2200.2680.2450.2560.2150.19735-390.2230.2280.1990.2090.1810.1670.19640-440.1550.1620.1440.1260.1090.1750.16445-50

0.140

0.136

0.127

0.115

0.111

0.169

0.161

P r e f e c t u r a l u n e m p l o y m e n t r a t e s (p e r c e n t )

1.27

1.69

2.36

1.51

1.02

2.43

1.08

N u m b e r o f o b s e r v a t i o n s

286,173

2,922

866

3,133

1,373

1,304

3,388

Table IX.

Sample statistics:urban women aged 25-50in 1990

IJM 31,2

156

V a r i a b l e

H a n H u i K o r e a n M a n c h u M o n g o l i a n U y g u r Z h u a n g

L a b o r f o r c e p a r t i c i p a t i o n r a t e

0.763

0.7210.6760.7210.7180.6480.836

E d u c a t i o n l e v e l ,p r o p o r t i o n w i t h ...P r i m a r y o r l e s s 0.2280.2270.0630.1700.1550.2710.320J u n i o r m i d d l e s c h o o l 0.4230.4090.4150.4450.3430.2950.411S e n i o r m i d d l e s c h o o l 0.2510.2630.3750.2550.3450.2860.196P o s t -s e c o n d a r y

0.098

0.1010.1460.1300.1570.148

0.073

M a r i t a l s t a t u s ,p r o p o r t i o n N o t m a r r i e d 0.0560.0600.1190.0640.0390.1080.086M a r r i e d ,s p o u s e n o t p r e s e n t

0.071

0.0760.0790.0380.0390.036

0.071

H o u s e h o l d c o m p o s t i o n ,m e a n N u m b e r o f a d u l t s (a g e d 18t)2.5092.5402.5102.5272.4162.6662.546N u m b e r o f c h i l d r e n a g e d 0-50.2220.2490.1580.2160.2590.3920.264N u m b e r o f c h i l d r e n a g e d 6-120.4070.4580.3120.3680.4430.6230.460N u m b e r o f c h i l d r e n a g e d 13-17

0.220

0.2340.2530.2530.248

0.238

0.250

A g e :p r o p o r t i o n i n e a c h c a t e g o r y 25-290.2110.2120.1620.2020.2700.2680.24630-340.2270.2050.1980.2280.1980.2470.23735-390.2100.2260.2690.2220.2050.2020.20840-440.1670.1610.1940.1810.1800.1510.14945-50

0.186

0.1960.1780.167

0.148

0.133

0.161

P r e f e c t u r a l u n e m p l o y m e n t r a t e s (p e r c e n t )

4.78

4.529.43

8.08

5.47

3.92

3.26

N u m b e r o f o b s e r v a t i o n s

88,332902253

843

440

332

659

Table X.

Sample statistics:urban women aged 25-50in

2000

Labor force participation

rates

157

从实践的角度探讨在日语教学中多媒体课件的应用

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Unit1 Americans believe no one stands still. If you are not moving ahead, you are falling behind. This attitude results in a nation of people committed to researching, experimenting and exploring. Time is one of the two elements that Americans save carefully, the other being labor. "We are slaves to nothing but the clock,” it has been said. Time is treated as if it were something almost real. We budget it, save it, waste it, steal it, kill it, cut it, account for it; we also charge for it. It is a precious resource. Many people have a rather acute sense of the shortness of each lifetime. Once the sands have run out of a person’s hourglass, they cannot be replaced. We want every minute to count. A foreigner’s first impression of the U.S. is li kely to be that everyone is in a rush -- often under pressure. City people always appear to be hurrying to get where they are going, restlessly seeking attention in a store, or elbowing others as they try to complete their shopping. Racing through daytime meals is part of the pace

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新大学日语简明教程课文翻译 第21课 一、我的留学生活 我从去年12月开始学习日语。已经3个月了。每天大约学30个新单词。每天学15个左右的新汉字，但总记不住。假名已经基本记住了。 简单的会话还可以，但较难的还说不了。还不能用日语发表自己的意见。既不能很好地回答老师的提问，也看不懂日语的文章。短小、简单的信写得了，但长的信写不了。 来日本不久就迎来了新年。新年时，日本的少女们穿着美丽的和服，看上去就像新娘。非常冷的时候，还是有女孩子穿着裙子和袜子走在大街上。 我在日本的第一个新年过得很愉快，因此很开心。 现在学习忙，没什么时间玩，但周末常常运动，或骑车去公园玩。有时也邀朋友一起去。虽然我有国际驾照，但没钱，买不起车。没办法，需要的时候就向朋友借车。有几个朋友愿意借车给我。 二、一个房间变成三个 从前一直认为睡在褥子上的是日本人，美国人都睡床铺，可是听说近来纽约等大都市的年轻人不睡床铺，而是睡在褥子上，是不是突然讨厌起床铺了？ 日本人自古以来就睡在褥子上，那自有它的原因。人们都说日本人的房子小，从前，很少有人在自己的房间，一家人住在一个小房间里是常有的是，今天仍然有人过着这样的生活。 在仅有的一个房间哩，如果要摆下全家人的床铺，就不能在那里吃饭了。这一点，褥子很方便。早晨，不需要褥子的时候，可以收起来。在没有了褥子的房间放上桌子，当作饭厅吃早饭。来客人的话，就在那里喝茶；孩子放学回到家里，那房间就成了书房。而后，傍晚又成为饭厅。然后收起桌子，铺上褥子，又成为了全家人睡觉的地方。 如果是床铺的话，除了睡觉的房间，还需要吃饭的房间和书房等，但如果使用褥子，一个房间就可以有各种用途。 据说从前，在纽约等大都市的大学学习的学生也租得起很大的房间。但现在房租太贵，租不起了。只能住更便宜、更小的房间。因此，似乎开始使用睡觉时作床，白天折小能成为椅子的、方便的褥子。

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新视野大学英语第一册Unit 1课文翻译 学习外语是我一生中最艰苦也是最有意义的经历之一。 虽然时常遭遇挫折，但却非常有价值。 我学外语的经历始于初中的第一堂英语课。 老师很慈祥耐心，时常表扬学生。 由于这种积极的教学方法，我踊跃回答各种问题，从不怕答错。 两年中，我的成绩一直名列前茅。 到了高中后，我渴望继续学习英语。然而，高中时的经历与以前大不相同。 以前，老师对所有的学生都很耐心，而新老师则总是惩罚答错的学生。 每当有谁回答错了，她就会用长教鞭指着我们，上下挥舞大喊：“错！错！错！” 没有多久，我便不再渴望回答问题了。 我不仅失去了回答问题的乐趣，而且根本就不想再用英语说半个字。 好在这种情况没持续多久。 到了大学，我了解到所有学生必须上英语课。 与高中老师不同，大学英语老师非常耐心和蔼，而且从来不带教鞭！ 不过情况却远不尽如人意。 由于班大，每堂课能轮到我回答的问题寥寥无几。 上了几周课后，我还发现许多同学的英语说得比我要好得多。 我开始产生一种畏惧感。 虽然原因与高中时不同，但我却又一次不敢开口了。 看来我的英语水平要永远停步不前了。 直到几年后我有机会参加远程英语课程，情况才有所改善。 这种课程的媒介是一台电脑、一条电话线和一个调制解调器。 我很快配齐了必要的设备并跟一个朋友学会了电脑操作技术，于是我每周用5到7天在网上的虚拟课堂里学习英语。 网上学习并不比普通的课堂学习容易。 它需要花许多的时间，需要学习者专心自律，以跟上课程进度。 我尽力达到课程的最低要求，并按时完成作业。 我随时随地都在学习。 不管去哪里，我都随身携带一本袖珍字典和笔记本，笔记本上记着我遇到的生词。 我学习中出过许多错，有时是令人尴尬的错误。 有时我会因挫折而哭泣，有时甚至想放弃。 但我从未因别的同学英语说得比我快而感到畏惧，因为在电脑屏幕上作出回答之前，我可以根据自己的需要花时间去琢磨自己的想法。 突然有一天我发现自己什么都懂了，更重要的是，我说起英语来灵活自如。 尽管我还是常常出错，还有很多东西要学，但我已尝到了刻苦学习的甜头。 学习外语对我来说是非常艰辛的经历，但它又无比珍贵。 它不仅使我懂得了艰苦努力的意义，而且让我了解了不同的文化，让我以一种全新的思维去看待事物。 学习一门外语最令人兴奋的收获是我能与更多的人交流。 与人交谈是我最喜欢的一项活动，新的语言使我能与陌生人交往，参与他们的谈话，并建立新的难以忘怀的友谊。 由于我已能说英语，别人讲英语时我不再茫然不解了。 我能够参与其中，并结交朋友。

新大学日语阅读与写作1 第3课译文

习惯与礼仪 我是个漫画家，对旁人细微的动作、不起眼的举止等抱有好奇。所以，我在国外只要做错一点什么，立刻会比旁人更为敏锐地感觉到那个国家的人们对此作出的反应。 譬如我多次看到过，欧美人和中国人见到我们日本人吸溜吸溜地出声喝汤而面露厌恶之色。过去，日本人坐在塌塌米上，在一张低矮的食案上用餐，餐具离嘴较远。所以，养成了把碗端至嘴边吸食的习惯。喝羹匙里的东西也象吸似的，声声作响。这并非哪一方文化高或低，只是各国的习惯、礼仪不同而已。 日本人坐在椅子上围桌用餐是1960年之后的事情。当时，还没有礼仪规矩，甚至有人盘着腿吃饭。外国人看见此景大概会一脸厌恶吧。 韩国女性就座时，单腿翘起。我认为这种姿势很美，但习惯于双膝跪坐的日本女性大概不以为然，而韩国女性恐怕也不认为跪坐为好。 日本等多数亚洲国家，常有人习惯在路上蹲着。欧美人会联想起狗排便的姿势而一脸厌恶。 日本人常常把手放在小孩的头上说“好可爱啊！”，而大部分外国人会不愿意。 如果向回教国家的人们劝食猪肉和酒，或用左手握手、递东西，会不受欢迎的。当然，饭菜也用右手抓着吃。只有从公用大盘往自己的小盘里分食用的公勺是用左手拿。一旦搞错，用黏糊糊的右手去拿，

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第10课 日本的季节 日本的一年有春、夏、秋、冬四个季节。 3月、4月和5月这三个月是春季。春季是个暖和的好季节。桃花、樱花等花儿开得很美。人们在4月去赏花。 6月到8月是夏季。夏季非常闷热。人们去北海道旅游。7月和8月是暑假，年轻人去海边或山上。也有很多人去攀登富士山。富士山是日本最高的山。 9月、10月和11月这3个月是秋季。秋季很凉爽，晴朗的日子较多。苹果、桔子等许多水果在这个季节成熟。 12月到2月是冬季。日本的南部冬天不太冷。北部非常冷，下很多雪。去年冬天东京也很冷。今年大概不会那么冷吧。如果冷的话，人们就使用暖气炉。 第12课 乡下 我爷爷住哎乡下。今天，我要去爷爷家。早上天很阴，但中午天空开始变亮，天转好了。我急急忙忙吃完午饭，坐上了电车。 现在，电车正行驶在原野上。窗外，水田、旱地连成一片。汽车在公路上奔驰。 这时，电车正行驶在大桥上。下面河水在流动。河水很清澈，可以清澈地看见河底。可以看见鱼在游动。远处，一个小孩在挥手。他身旁，牛、马在吃草。 到了爷爷居住的村子。爷爷和奶奶来到门口等着我。爷爷的房子是旧房子，但是很大。登上二楼，大海就在眼前。海岸上，很多人正在全力拉缆绳。渐渐地可以看见网了。网里有很多鱼。和城市不同，乡下的大自然真是很美。 第13课 暑假 大概没有什么比暑假更令学生感到高兴的了。大学在7月初，其他学校在二十四日左右进入暑假。暑假大约1个半月。 很多人利用这个假期去海边、山上，或者去旅行。学生中，也有人去打工。学生由于路费等只要半价，所以在学期间去各地旅行。因此，临近暑假时，去北海道的列车上就挤满了这样的人。从炎热的地方逃避到凉爽的地方去，这是很自然的事。一般在1月、最迟在2月底之前就要预定旅馆。不然的话可能会没有地方住。 暑假里，山上、海边、湖里、河里会出现死人的事，这种事故都是由于不注意引起的。大概只能每个人自己多加注意了。 在东京附近，镰仓等地的海面不起浪，因此挤满了游泳的人。也有人家只在夏季把海边的房子租下来。 暑假里，学校的老师给学生布置作业，但是有的学生叫哥哥或姐姐帮忙。 第14课 各式各样的学生 我就读的大学都有各种各样的学生入学。学生有的是中国人，有的是美国人，有的是英国人。既有年轻的，也有不年轻的。有胖的学生，也有瘦的学生。学生大多边工作边学习。因此，大家看上去都很忙。经常有人边听课边打盹。 我为了学习日本先进的科学技术和日本文化来到日本。预定在这所大学学习3年。既然特意来了日本，所以每天都很努力学习。即便如此，考试之前还是很紧张。其他学生也是这

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教育界的科技革命 如果让生活在年的人来到我们这个时代，他会辨认出我们当前课堂里发生的许多事情——那盛行的讲座、对操练的强调、从基础读本到每周的拼写测试在内的教学材料和教学活动。可能除了教堂以外，很少有机构像主管下一代正规教育的学校那样缺乏变化了。 让我们把上述一贯性与校园外孩子们的经历作一番比较吧。在现代社会，孩子们有机会接触广泛的媒体，而在早些年代这些媒体简直就是奇迹。来自过去的参观者一眼就能辨认出现在的课堂，但很难适应现今一个岁孩子的校外世界。 学校——如果不是一般意义上的教育界——天生是保守的机构。我会在很大程度上为这种保守的趋势辩护。但变化在我们的世界中是如此迅速而明确，学校不可能维持现状或仅仅做一些表面的改善而生存下去。的确，如果学校不迅速、彻底地变革，就有可能被其他较灵活的机构取代。 计算机的变革力 当今时代最重要的科技事件要数计算机的崛起。计算机已渗透到我们生活的诸多方面，从交通、电讯到娱乐等等。许多学校当然不能漠视这种趋势，于是也配备了计算机和网络。在某种程度上，这些科技辅助设施已被吸纳到校园生活中，尽管他们往往只是用一种更方便、更有效的模式教授旧课程。 然而，未来将以计算机为基础组织教学。计算机将在一定程度上允许针对个人的授课，这种授课形式以往只向有钱人提供。所有的学生都会得到符合自身需要的、适合自己学习方法和进度的课程设置，以及对先前所学材料、课程的成绩记录。 毫不夸张地说，计算机科技可将世界上所有的信息置于人们的指尖。这既是幸事又是灾难。我们再也无须花费很长时间查找某个出处或某个人——现在，信息的传递是瞬时的。不久，我们甚至无须键入指令，只需大声提出问题，计算机就会打印或说出答案，这样，人们就可实现即时的"文化脱盲"。 美中不足的是，因特网没有质量控制手段；"任何人都可以拨弄"。信息和虚假信息往往混杂在一起，现在还没有将网上十分普遍的被歪曲的事实和一派胡言与真实含义区分开来的可靠手段。要识别出真的、美的、好的信息，并挑出其中那些值得知晓的, 这对人们构成巨大的挑战。 对此也许有人会说，这个世界一直充斥着错误的信息。的确如此，但以前教育当局至少能选择他们中意的课本。而今天的形势则是每个人都拥有瞬时可得的数以百万计的信息源，这种情况是史无前例的。 教育的客户化 与以往的趋势不同，从授权机构获取证书可能会变得不再重要。每个人都能在模拟的环境中自学并展示个人才能。如果一个人能像早些时候那样"读法律"，然后通过计算机模拟的实践考试展现自己的全部法律技能，为什么还要花万美元去上法学院呢？用类似的方法学开飞机或学做外科手术不同样可行吗？ 在过去，大部分教育基本是职业性的：目的是确保个人在其年富力强的整个成人阶段能可靠地从事某项工作。现在，这种设想有了缺陷。很少有人会一生只从事一种职业；许多人都会频繁地从一个职位、公司或经济部门跳到另一个。 在经济中，这些新的、迅速变换的角色的激增使教育变得大为复杂。大部分老成持重的教师和家长对帮助青年一代应对这个会经常变换工作的世界缺乏经验。由于没有先例，青少年们只有自己为快速变化的"事业之路"和生活状况作准备。