Women, Men, and the Global Quality of Life
The status of women can be a better predictor of a nation’s general quality of life than GDP--so found the 1995 CPS study Women, Men, and the Global Quality of Life (by Riane Eisler, David Loye, and Kari Norgaard) which examined statistical data from 89 nations.
Women, Men, and the Global Quality of Life, published in 1995 in time for the Beijing United Nations Women’s Conference, conclusively showed why we need new economic measurements—economic indicators that take into account the social construction of gender roles and relations as a key variable in how a society develops and allocates its resources.
The aim of our study was to use both quantitative and qualitative data to examine whether the way a society structures the relations between the female and male halves of humanity impacts its quality of life.
The study supports the common sense conclusion that gender equity or inequity (that is, systematic discrimination and violence against women and female children) is a key factor in the overall quality of life, not only for women, but also for men and children of both genders.
purchase Women, Men, and the Global Quality of Life a 1995 report of the Gender Equity and Quality of Life Project of the Center for Partnership Studies by Riane Eisler, David Loye, and Kari Norgaard.
The following excerpts from Women, Men, and the Global Quality of Life will help you to understand the main conclusions of the CPS. The statistical tables, statistical analysis, and detailed discussion of findings are available in the whole report.
Why we need new measures and new policies
Until now, development has primarily been measured in terms of such conventionally accepted indicators as Gross Domestic Product (GDP) and Gross National Product (GNP). Although these measures provide information about a society's economic resources and potential for supporting human development, they have in recent years been severely critiqued for their failure to take into account the hidden environmental and human costs of the “productivity” they measure. Moreover, there is increasing evidence that new measures of development are needed because of sizeable variations in such basic indicators of human welfare as infant mortality, maternal mortality, and life expectancy in countries with similar GDP.
Infant Mortality, Maternal Mortality, and Life Expectancy
United Nations Human Development Reports show that nations with very close (in some cases almost identical) GDPs show wide variations in maternal and infant mortality rates. The following pairs of countries from the 1994 edition are cases in point.
- Hong Kong (GDP 18,520 U.S.$), maternal mortality of 6 women per 100,000 live births
United Arab Emirates (GDP 17,000 U.S.$), maternal mortality of 130 women per 100,000 live births — over twenty times the rate of Hong Kong.
- France (GDP 13,960 U.S.$), infant mortality rate of 8 infants per 1,000 live births
Kuwait (GDP 13,840 U.S.$), infant mortality rate of 19 infants per 1,000 live births—over double the rate of France.
- Costa Rica (GDP 3,760 U.S.$), maternal mortality of 26 women for every 100,000 live births
South Africa (GDP 4,980 U.S.$), maternal mortality of 550 women for every 100,000 live births — over twenty times the rate of Costa Rica.
Using the conventional assumption that GDP determines quality of life, one would predict that countries with higher GDPs would also be at the bottom of the maternal mortality rates. The following pairs of countries disprove that assumption.
- Japan (GDP of 19,390 U.S.$), with one of the highest GDPs in the world, has a maternal mortality rate four times that of Norway (GDP 17,170 U.S
- Ireland (GDP 11,430 U.S.$), maternal mortality rate of 3 per 100,000 live births
Singapore (GDP 14,734 U.S.$) maternal mortality rate of 14 per 100,000 live births — almost five times that of Ireland.
Using GDP as the predictor one would accurately predict that in Ethiopia, with an extremely low GDP (450 U.S.$ in 1990) the life expectancy would be low (it is only 42 years). But one would not predict that in India, with a GDP that is more than double (1050 U.S.$ in 1990), 25 percent of girls die before they reach the age of 15. Nor would one predict that in the affluent United Kingdom, which had a GDP of 13,060 U.S.$, 196,000 children would be homeless in 1991. Or that in the United States (which had a GDP of 19,850 U.S.$), 13 per cent of the population would live below the poverty line in 1991, with 16.1 per cent, or 41 million people, without health insurance in 1993.
This is not to say there is no relationship between a low GDP and such basic indicators of the quality of life as rates of infant and maternal mortality, lack of drinkable water, lack of adequate health care, lack of contraceptive availability, and low literacy rates. Obviously, countries with a low GDP have fewer economic resources for these purposes. However, as the previous examples show, a higher quality of life does not necessarily follow a higher GDP.
Global population growth: It’s not just a “women’s issue”
Our global population is growing at a fantastic rate, with projections that, if present rates of population growth continue, more people will be added to our planet in one year during the middle of the 21st century than during the entire first 1500 years after the date assigned to the death of Jesus. It is also well known that overpopulation is a major factor in all the ecological, social, and political problems of our time — in other words, in worsening the quality of life.
Although this was not formally acknowledged until the 1994 United Nations Population Conference in Cairo, it is also well known that the “women's issues” of reproductive freedom of choice and creating the opportunities and motivations for women to limit birth through greater gender equity are central to any viable approaches to overpopulation. Studies show that education for women is probably the most cost-effective approach to halting what is quite accurately described as the global population explosion.
Human Rights and Environmental Degradation
The data on human rights also contradict common assumptions that a better quality of life is a direct function of economic development. For example, using respect for human rights as an indicator of human development, we find that countries as rich as Saudi Arabia and as poor as Haiti both have extremely high levels of human rights violations.
Moreover, while wars (particularly prolonged civil wars, with their enormous economic and human costs, including widespread famine) have been more frequent in the poorer South, generally they have been fought with weapons and sometimes also personnel from the more affluent North. And violent crime, with its huge economic and human costs, is also a major problem in rich nations such as the U.S.A.
Furthermore, problems of environmental degradation also plague both the affluent and poor regions of our world. In fact, according to the 1991 Human Development Report, “significant environmental degradation is usually caused by poverty in the South—and by affluence in the North.”
The questions we need to answer are these:
- Why are rich and poor nations alike confronted by poverty and other chronic causes of human suffering?
- If wealth and poverty alike can lead to environmental damage, institutionalized violence, and chronic violations of human rights, how can we achieve real development?
- If GDP and GNP are not accurate indicators of development, how can we fashion more reliable and effective measures?
- Most importantly, how can quality of life and its gender correlate be recognized as the critical factor in development?
Our Gender-Holistic, Domination and Partnership Systems Approach
The Gender Equity and Quality of Life Project began as a response to these kinds of questions — to look at the economic, ecological, and social crises that plague our planet from a new integrated perspective. It proceeds from the premise that what is needed are new analytical tools deriving from a new type of analysis focusing on how differences in social structures and value systems affect not only economic production but also the rate and direction of resources allocation. According to the cultural transformation theory developed by Riane Eisler, because humanity is composed of two halves — women and men — the social construction of gender roles and relations must be factored into social and economic analyses as a key variable in a society's institutions, values, and the development and allocation of economic resources.
Cultural transformation theory is the outcome of two decades of multidisciplinary research using what Eisler calls a gender-holistic approach: one that draws from a database that, unlike the conventional male-centered analyses, gives equal weight to information about the female and male halves of humanity. This approach also makes it possible to identify patterns or configurations that cannot be seen in analyses where anything relating to gender is either ignored or treated as an isolated “women's issue.”
Using this methodology, Eisler studied societies that on the surface seem very different — varying greatly in terms of level of technological development, geographical location, religion, racial or ethnic composition, and placement in history. Eisler observed that societies characterized by rigid male dominance also tend to be generally hierarchic and authoritarian with a correspondingly high level of institutionalized social violence; she described these as domination systems. Eisler also observed that societies characterized by greater gender partnership tend to be generally more democratic and egalitarian, with less institutionalized social violence; she described these as partnership systems.
She also noted that in societies that orient primarily to the domination system humanity is divided into a male in-group (as reflected in words like “mankind”) and a female out-group (or “other”), with women and anything labeled feminine given lower value than anything associated with the “superior” male in-group or labeled “masculine.” By contrast, in societies orienting more toward the partnership model women and values and activities that in dominator societies are stereotypically considered feminine (such as caretaking and environmental housekeeping) need not be devalued and can instead be given social and economic support.
On the basis of these kinds of findings of a strong connection between how a society structures the roles and relations of women and men and its overall socio-economic structure and system of values, Eisler predicted that the degree to which a society orients primarily to the partnership system (distinguished by gender equity) or the domination system (in which gender inequity prevails) will show a close correspondence to the degree to which a higher or a lower general quality of life prevails.
This study was undertaken to test this prediction. Our hypothesis was that there is a statistically significant correlation between gender equity and inequity and a higher or lower quality of life for all. To test this hypothesis quantitatively, we used statistical procedures to analyze data (most of which have only become available during the last half decade) about most of the nations in our world. To analyze our results, we drew from a variety of sources, including recent works by scholars examining economics from a perspective in which, to paraphrase a recent book title, “women count.” We also utilized the templates of the partnership and domination systems as dynamic analytical tools that take into account the complex interactions between various elements in a social system.
Such interactive or systems approaches, sometimes associated with chaos theory and non-linear dynamics, have been applied in recent years by scientists in a number of fields: in chemistry by Ilya Prigogine and Isabelle Stengers, in mathematics by Ralph Abraham, in biology by Humberto Maturana and Vilmos Czanyi, and in the social sciences by two of the authors, Loye and Eisler. One of the great advantages of this approach is that it makes it possible to view living systems not as static but as dynamic. It further makes it possible to make a distinction between simple linear cause and effect relations and more complex interactive systems relations.
For example, one could hypothesize that with certain gender equity variables there may be a direct causal relationship with certain higher quality of life variables. To illustrate, one might predict that greater access by women to health care will probably result in a generally higher level of health (both because the female half of the population will be healthier and because healthier women give birth to healthier children). Or one could predict that a higher female literacy rate will result in a generally higher literacy rate (since most of the nations with the lowest literacy rates also have the highest gaps between male and female literacy).
But the way social systems function is much more complex than through simple linear causes and effects. This is why the main focus of our study design and discussion will be on what is called systems self-organization, or the long-range interaction between interdependent and mutually reinforcing components of a social system.
But before proceeding to the design of our study, its results, and our discussion, we want to briefly touch on a few other introductory points. The first is that when we speak of the social construction of gender roles and relations, we mean just that. Obviously there are biological differences between women and men, but this does not mean that the roles and relations between women and men are invariable or inherent. Rather, most of what is stereotypically considered “masculine” or “feminine” is primarily a matter of learning or socialization — as illustrated by the systematic teaching to boys of violent behaviors through war toys and games and the fact, as scientific experiments have shown, that even female monkeys do not “instinctively” know nurturing behaviors, but also have to learn how to be mothers.
A second point is that we consider this study a first probe that we hope may lead others to apply a gender-holistic approach to economic, social, and environmental analyses and action. For example, we would have liked to directly test another hypothesis based on cultural transformation theory: that if there is systematic violence and discrimination against half a nation's population, not only will the average quality of life in that nation be significantly lowered, but this will also significantly affect attitudes and practices relating to violence and discrimination in general, which results in lowering the general quality of life even further. Unfortunately, there are as yet no adequate measures for assessing the variables of violence and discrimination against women globally. In the discussion, however, we will return to this issue because of its key importance within the context of this study as a whole.
Thirdly, we want to here make explicit something that has been implicit in the foregoing. This is that the argument can be made that the conclusion that gender inequity has adverse effects on the general quality of life is so obvious that a study to test such a hypothesis is superfluous.
As approximately half the population of every nation is female, it seems self-evident that the result of gender inequity is a far lower overall quality of life than would exist were gender equity the norm. The first United Nations Decade for Women (1975-1985), spurred a significant body research and publications on these questions. There is now ample documentation that, as Charlotte Bunch writes, “significant numbers of the world's population are routinely subject to torture, starvation, terrorism, humiliation, mutilation, and even murder simply because they are female.”
But while these connections may seem obvious to some, this is true only for feminist scholars and a handful of economic, social and political experts in developmental policy. For the overwhelming majority of those who shape or in other ways influence global development policy and action, these connections are neither perceived nor considered important enough to bother with.
Our Methods and Measures
The Challenge of GNP and GDP as Measures
Like gender equity, quality of life is a relatively new concept in economic thinking. The conventional approach to economic measurement focused on production, as in Gross National Product (GNP) and Gross Domestic Product (GDP). Originally GNP and GDP were intended to serve as indicators of economic activity. But on the assumption that as wealth increases so does the quality of life, with time they also came to be interpreted as gross measures not only of development but also the quality of life.
Nonetheless, GNP and GDP are not adequate measures of quality of life, or even of productivity. For instance, GDP and GNP generally include only productivity in the formal economy, and thus leave out all the activities that are not monetized and/or not reported for official records. This is in fact a huge segment of every nation's economic activity. Not only that, these measures provide no information about how goods and services (including such basics as food, health care, and education) are distributed, and the impact of this on people's lives. Moreover, in many ways GDP and GNP include activities that actually worsen, rather than improve, the quality of life, as they fail to take into account environmental, health, and other costs of so-called productive activities, and thus ignore their negative effects on the quality of life. As Hazel Henderson wryly put it, they include not just “goods” but “bads.”
Recognition of these problems led to the search for new more fine-tuned measures. One of the earliest results of this search was the Physical Quality of Life Index, or PQLI, developed in the 1960s by the Society for International Development. More recently, in 1990, the United Nations began to issue Human Development Reports. A number of international agencies have also begun to monitor human rights violations. Environmental problems, such as deforestation and desertification, are also increasingly being monitored.
In many respects these are very useful indicators of the real conditions in a society, as they provide data not just about business ledgers but about people's real lives. However, they still by and large fail to address another major inadequacy of the conventional GDP and GNP approach. Just as GNP and GDP fail to include in their statistical models the socially essential work of women — performed in homes, as volunteers, and in large world regions such as Africa as subsistence farmers whose production is essential for survival — to date most of these newer statistical measures still do not adequately take into account the relative situation of men and women, even in regard to such vital quality of life factors as women's economic and social equality.
Thus, we had to look elsewhere to test our hypothesis that there is a correlation between gender equity or inequity and both the general quality of life and the underlying health of our economies. Fortunately, as a result of the research and publications spurred by the first United Nations Decade for Women (1975-1985), more and more data about women have begun to appear. What these reveal is that there are indeed many differences in the lives (and deaths) of women and men — differences that may be used to measure whether countries are high, middle, or low in their degrees of gender equity.
However, for neither gender equity nor general quality of life were we able to find an existing battery of measures suitable for our purposes. Hence, we had to construct our own. In so doing, we did not completely discard more conventional economic measures such as GDP. But while we included GDP, we used it only as one of a number of measures of quality of life.
Selecting Gender Equity and Quality of Life Variables
The task we faced in developing our measurement database was to find the best sources for our variables and to then select those most descriptive of quality of life and gender equity. We also wanted to include only those variables that could meet two basic criteria:
- they must be available for the widest possible range of the nations of this earth
- they must be as rigorously quantified and validated as possible.
We identified seven statistical sources that best met our criteria. From these sources we gathered data for 22 variables (9 measures of gender equity and 13 measures of quality of life) from a total of 89 countries.
- Gender gap variables
Number of literate females for every 100 literate males (coded FM_LITCY in Appendices).
Female life expectancy as a percentage of male life expectancy (coded FM_LFEXP).
Number of women in parliament for every 100 men in parliament (FM_POLIT).
Number of females in secondary education for every 100 males (FM_ENROL).
- Woman specific variables
Maternal mortality (MATMORT).
Contraceptive prevalence (CONTRACP).
Access to abortion (ABORTION).
Social equality for women (SOCEQUA).
Economic equality for women (ECONQUAL).
- Quality of life variables
Overall life expectancy (coded LIFE_EXP in the Appendices).
Human rights rating (HRIGHT).
The percentage of the population with access to health care (HEALTH).
The percentage of the population with access to clean water (WATER).
Overall literacy rate (LITERACY).
Infant mortality rate (INFMORT).
Number of refugees fleeing the country (REFUGES).
Percentage of daily caloric requirements citizens consume (PERCAL).
Per capita Gross Domestic Product (GDP_PER).
Percentage of GNP distributed to poorest 40 percent of households (LOW40).
Ratio of GDP distributed to the wealthiest 20 percent of the population to percentage distributed to the poorest 20 percent of the population (HIGH_LOW).
Percentage of forest habitat remaining (FOREST).
Compliance with Convention on International Trade in Endangered Species (SPECIES).
Some of the variables display a certain degree of overlap or in-built interdependency. For example, there would be overlap to some degree in the relation of F/M literacy to overall literacy, female life expectancy to overall life expectancy, and maternal mortality to overall life expectancy and infant mortality. Given the great difficulties we faced in obtaining variables for which data was available across a reasonably wide and representative range of countries, we decided it was better to accept some interdependency than to eliminate variables of basic importance and utility. Even though multi-colinearity may be involved, omission of a significant variable would cause specification error, a much worse problem.
—many studies examining the central role of gender equity or inequity in social systems will be carried out by other researchers, and that our gender-holistic, systems framework will be useful to this end
—the materials presented in this study will help accelerate the development of more gender-holistic (and thus, more effective) approaches to the increasingly urgent problems of economic and human development facing our globe today
—these data can provide support for the efforts of gender-conscious policy makers and advisors — not only women, but men with proven commitment to these goals in their efforts to formulate and implement economic and social policies that can lead to a higher quality of life for all.
One of our primary conclusions is that a gender-specific approach to economic analysis is urgently needed to provide policy makers with the database required for properly informed policy choices. Such a database can help dispel many fictions still perpetuated by conventional economic measures. One example is the fiction that only the activities of men in the so-called formal or monetized economy are significant in relation to economic development. Another is the fiction that economic measures that leave out the contribution of women in the so-called informal or unpaid economy are accurate guidelines for effective policy planning. Still another is the fiction that policies addressing such critical development issues as child nutrition can be successful by merely treating the household as a unit where resources will be distributed by the male “head” for everyone's equal benefit.
It is therefore imperative that funding for projects applying a gender-holistic perspective to problems of economic and human development no longer be confined to the small allocations made for so-called “feminist research.” Equally imperative is that educational institutions and departments of colleges and universities offering courses in both economics and economic development redesign their curricula to correct the present male-centered orientation.
But having said this, we want to proceed to an even more urgent matter. This is that social and economic policy-makers clearly cannot wait for such a fundamental shift in academic orientation to make their policy choices more effective. They need to immediately begin to address gender inequity as a top policy priority.
Logic dictates that national and international policies make programs that promote greater gender equity a top priority. Similarly, given all the data showing that women and children are not only the poorest of the world's poor, but the majority of the world's hungry and poor, logic dictates that national and international policies make programs dealing with the poverty and hunger of women and children a top priority.
Because many of our world leaders still systematically ignore those human issues that are called “women's issues,” to date none of this has come to pass. On the contrary, so-called structural adjustment policies, which cut social services for nutrition, health care, and education, have disproportionately impacted women in very adverse ways, increasing not only their poverty, but their work burdens — since the underlying assumption is once again that women will somehow make up for these cuts by doing this work for free. The entry of more women into leadership positions is gradually beginning to focus more attention on some of these “gender issues.” Still, because most of those in decision making positions are still male at this time, no real changes in policy — and with this, resources allocation — can be expected in the near future unless substantial numbers of male leaders also become aware of the magnitude of the personal, political, and economic discrimination against women worldwide, and even more specifically, of the relation between gender equity or inequity and the overall quality of life.
Because gender inequity so adversely impacts the lives — and all too often, deaths — of female children and women, it should of course be enough to say that policies to end patterns of systematic gender-based violence and discrimination should be a top policy priority for both national governments and international agencies. Particularly this should apply to the United Nations, which in its charter urges all member nations to respect “human rights and fundamental freedoms.” But despite the United Nations Convention on the Elimination of All Forms of Discrimination Against Women, neither the United Nations nor any world nation have made the ending of discrimination and violence against the female half of the population a top priority.
Already more than a century ago germinal thinkers such as Elizabeth Cady Stanton, Karl Marx, John Stuart Mill, and Charles Fourier, intuited that the status of women is a good predictor of the general development of a society — in Fourier's words, that the degree of emancipation of women is an index of the degree of a society's emancipation.