Gender data gap

from Wikipedia, the free encyclopedia

The gender data gap is the determination that data collection procedures that are socially, economically or medically relevant mostly only contain data on men. In addition, the term also describes the lack of surveys that only concern women, but which would have economic and political consequences, such as B. the amount of unpaid work in household chores or in bringing up children and caring for relatives. The term is part of a series of “ gender gaps ” that have been identified in connection with gender studies over the past 20 years and that point to the institutionally disadvantaged situation of women in society.

Origin of the term

When dealing with statistical data on the population and the level of development of the member countries, it became clear within the UN that important data on the situation of women, such as educational level , domestic violence and income, were not statistically recorded. The Inter-Agency and Expert Group in Gender Statistics was founded in 2006 with the aim of educating institutions and countries about the relevance of such data collections .

In the document, the Inter-Agency and Expert Group in Gender Statistics sets itself the goal of "to review and identify key initiatives and programs that support and enhance national statistical offices' capacity to develop gender statistics" so that gender data can be collected more systematically. With this, the group intended to close the gender data gap in country statistics.

Since then, more and more statistical institutions have been dealing with the topic and trying to close the gap. The term became more common to the general public in 2019 with the publication of Caroline Criado Perez's book Invisible Women .

Gender differences in data collection

Pharmaceutical research

Pharmacy is research developed for the common good. But research differs between the sexes. In order to bring a drug onto the market, it has to be tested repeatedly and precisely. The approval of the drug is limited to the gender of the people tested. For example, drugs that have only been tested on women are only permitted for women. In some cases, such as For example, osteoporosis and blood cancer , the treatment has only been tried on one sex, although the opposite sex is also affected. If one looks at the general distribution of men and women who take part as test persons, it is noticeable that the proportion of men is significantly higher than that of women. This is due to one major reason: hormones. Medicines should be tested without any influence of hormones. The behavior of a drug depends more on individual circumstances than on gender. Thus, for example, trained people react differently to the same active ingredient than untrained people. The results of the gender-specific evaluation show that the difference lies in the dosage of a drug. These differences are recorded on the G-BA website and in the European public assessment reports (EPARs).

medicine

Another problem is the often incorrect diagnoses made by some doctors in female patients. The female body reacts differently to certain illnesses and injuries than the male. Nevertheless, the male body and its symptoms are mostly taken as a reference for the female. This can lead to life-threatening misdiagnoses in women, which could be avoided with a gender-specific consideration.

Algorithms

The gender data gap is also evident in modern algorithms and AI systems . This is because these algorithms are developed by their authors with specific information and functions. If information is missing from the inventors, this cannot be included in the algorithm. Because of this, there are many so-called " health trackers " that are not able to record a woman's menstrual cycle. The technologies reflect society in terms of values ​​and knowledge. This is why some algorithms associate cooking-related images with women rather than men. The consequences of the one-sided system are also noticeable financially. Men, for example, are often given a higher credit card limit even though their creditworthiness is lower than that of women.

product design

In her book, Caroline Criado Perez lists a number of products that are based on data on the male body and are less suitable for women: stoves that require more work from women, cell phones that are too big for women's hands, ergometers that are not reliable Provide data on women's performance. In product development, it is increasingly pointed out that gender aspects must be taken into account in product design. As early as 2006, the Fraunhofer Institute for Systems and Innovation Research published a study that showed that certain products require special consideration of gender aspects: household appliances, computer games, care robots, airbags. The focus is not only on the safety aspect, as in the case of accidents with cars or household appliances that are not ergonomic enough for the woman's body, but also whether products are adapted to female spatial orientation or whether certain stereotypes are reinforced as a result. Certain gender aspects have to be identified so that relevant data (female anatomy, needs, expectations, user behavior) can be collected through experiments, observations and interviews, which can be incorporated into the product design.

Book Invisible Women by Caroline Criado Perez

Although the UN has been trying to create more publicity for the topic since 2006, the book Invisible Women caused a new wave in the discussion about the gender gap in 2019. Through a series of interviews, reviews and reports, the topic has reached the general public and brought the academic and feminist discussion to television and Feulleitons . With extensive research, the author Caroline Criado Perez shows how women are not only disadvantaged in the labor market, but are also negatively affected by a data situation that is mostly based on guide values for men. The topic reveals methodological problems in studies and limit values ​​in science and technology and is extremely relevant because of its social implications for the situation of women.

Role of the UN

An agenda for sustainable development up to 2030 was signed by 193 UN member states in 2015 . The aim is to consider economic, social and ecological dimensions for sustainable development. At the heart of the agenda are 17 Sustainable Development Goals (SDGs) for more sustainable development. All three dimensions are taken into account: social , environmental , economic . In addition, 232 indicators were worked out. 54 of these indicators are gender specific.

UN Women

In relation to the Agenda for Sustainable Development 2013, UN Women has taken up the existing gender data gap: “The monitoring of the SDGs from the gender perspective is limited by three main challenges: firstly, the unequal recording of gender-specific indicators (...), secondly, gaps in the gender-specific ones Data and, thirdly, the quality and comparability of the available data across countries and over time. "

The UN Women cites the following reasons for the lack of collection of gender-specific data:

  1. Countries would invest too little in collecting gender statistics
  2. There is a knowledge gap in collecting data on new and emerging topics

Euro NCAP

The Euro NCAP (German: "European New Car Assessment Program") changed its procedure in 2016. Since then, the results of the women's dummies have also been included in the star ratings of new cars. In addition, the UNECE (United Nations Economic Commission for Europe) is advising on a new test regulation that should offer women and older people better occupant protection.

Perspectives

If gender equality continues at the current pace, then according to the Gender Gap Report of the World Economic Forum 2020, economic equality would last 257 years and political equality 94.5 years. In the area of ​​education, the duration until equality is achieved is limited to 12 years. In general, the number of the total gender gap varies annually. According to the latest findings, the World Economic Forum expects 99.5 years to reach gender equality in 2020.

Individual evidence

  1. ↑ a b Inter-Agency and Expert Group in Gender Statistics. 2013, accessed July 29, 2020 .
  2. ↑ oA: gender- differences -in-the-drug- effect . Retrieved July 14, 2020 .
  3. ↑ Vera Regitz-Zargosek: Why do we need gender medicine? Retrieved June 22, 2020 .
  4. ↑ Caroline Criado Perez: We Need to Close the Gender Data Gap By Including Women in Our Algorithms. Retrieved June 22, 2020 .
  5. ^ A b c Caroline Criado Perez: Invisible Women Exposing Data Bias in a World Designed for Men . Penguin, London 2019, ISBN 978-1-78470-628-9 , pp. 177 .
  6. ↑ a b Susanne Bührer: Examples for gender and diversity aspects . In: Susanne Bührer Martina Schraudner (Ed.): Gender aspects in research How can gender aspects be recognized and assessed in research projects? Fraunhofer Institute for Systems and Innovation Research, Karlsruhe 2006, p. 170-174 .
  7. ↑ GrrlScientist: Invisible Women: Exposing Data Bias In A World Designed For Men. Accessed August 24, 2020 .
  8. ^ Süddeutsche Zeitung: Review - Caroline Criado-Perez: "Invisible Women". Retrieved August 24, 2020 .
  9. ↑ Federal Ministry for Economic Cooperation and Development (2017): The future contract for the world. The 2030 Agenda for Sustainable Development. Retrieved July 14, 2020 .
  10. ↑ Making women and girls visible: Gender data gaps and why they matter. Retrieved July 29, 2020 .
  11. ↑ Man scale. March 21, 2016, accessed June 21, 2020 .
  12. ↑ Hedda Nier: 99.5 years to gender equality. Retrieved July 14, 2020 .