Building Feminist Economies is about creating a world with clean air to breath and water to drink, with meaningful labour and care for ourselves and our communities, where we can all enjoy our economic, sexual and political autonomy.
In the world we live in today, the economy continues to rely on women’s unpaid and undervalued care work for the profit of others. The pursuit of “growth” only expands extractivism - a model of development based on massive extraction and exploitation of natural resources that keeps destroying people and planet while concentrating wealth in the hands of global elites. Meanwhile, access to healthcare, education, a decent wage and social security is becoming a privilege to few. This economic model sits upon white supremacy, colonialism and patriarchy.
Adopting solely a “women’s economic empowerment approach” is merely to integrate women deeper into this system. It may be a temporary means of survival. We need to plant the seeds to make another world possible while we tear down the walls of the existing one.
We believe in the ability of feminist movements to work for change with broad alliances across social movements. By amplifying feminist proposals and visions, we aim to build new paradigms of just economies.
Our approach must be interconnected and intersectional, because sexual and bodily autonomy will not be possible until each and every one of us enjoys economic rights and independence. We aim to work with those who resist and counter the global rise of the conservative right and religious fundamentalisms as no just economy is possible until we shake the foundations of the current system.
Advance feminist agendas: We counter corporate power and impunity for human rights abuses by working with allies to ensure that we put forward feminist, women’s rights and gender justice perspectives in policy spaces. For example, learn more about our work on the future international legally binding instrument on “transnational corporations and other business enterprises with respect to human rights” at the United Nations Human Rights Council.
Mobilize solidarity actions: We work to strengthen the links between feminist and tax justice movements, including reclaiming the public resources lost through illicit financial flows (IFFs) to ensure social and gender justice.
Build knowledge: We provide women human rights defenders (WHRDs) with strategic information vital to challenge corporate power and extractivism. We will contribute to build the knowledge about local and global financing and investment mechanisms fuelling extractivism.
Create and amplify alternatives: We engage and mobilize our members and movements in visioning feminist economies and sharing feminist knowledges, practices and agendas for economic justice.
“The corporate revolution will collapse if we refuse to buy what they are selling – their ideas, their version of history, their wars, their weapons, their notion of inevitability. Another world is not only possible, she is on her way. On a quiet day, I can hear her breathing”.
Arundhati Roy, War Talk
Please visit the "Funding ideas" page to get some ideas and inspiration for how you can fund your participation at the next Forum, including the limited support AWID will be able to provide.
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Listen to the story here:
Cooperativa Textil Nadia Echazú
"My dreams and objectives have always been the same as those of Lohana Berkins: for the cooperative to continue standing and not to close. To continue to give this place to our travesti comrades, to give them work and a place of support"
Brisa Escobar,
president of the Cooperative
Guadalupe was an environmental activist involved in the fight against crime in Cherán, Mexico.
Guadalupe helped to overthrow the local government in April 2011 and participated in local security patrols including those in municipal forests. She was among the Indigenous leaders of Cherán, who called on people to defend their forests against illegal and merciless logging. Her work for seniors, children, and workers made her an icon in her community.
She was killed in Chilchota, Mexico about 30 kilometers north of her hometown of Cherá.
The Sex Workers' Trade Union Organisation (Organización de Trabajo Sexual, OTRAS) is the first union of sex workers in the history of Spain. It was born out of the need to ensure social, legal and political rights for sex workers in a country where far-right movements are on the rise.
After years of struggles against the Spanish legal system and anti-sex workers groups who petitioned to shut it down, OTRAS finally obtained its legal status as a union in 2021.
Its goal? To decriminalize sex work and to ensure decent working conditions and environments for all sex workers.
The union represents over 600 professional sex workers, many of whom are migrant, trans, queer and gender-diverse.
Ces défenseuses ont fait campagne pour les droits fonciers et ont lutté pour les droits des femmes et des peuples autochtones. Elles se sont opposées aux industries extractives, ont écrit de la poésie et se sont battues pour que l'amour prévale. L'une d'entre elles nous a quitté il y a dix-neuf ans. Nous vous invitons à vous joindre à nous pour rendre hommage à ces défenseuses, à leur travail et à l’héritage qu’elles nous ont laissé. Faites circuler ces mèmes auprès de vos collègues et amis ainsi que dans vos réseaux et twittez en utilisant les hashtags #WHRDTribute et #16Jours.
S'il vous plaît cliquez sur chaque image ci-dessous pour voir une version plus grande et pour télécharger comme un fichier
Anna grew up in Lewes, Sussex (UK) and, after deciding not to pursue her English degree at Sheffield University, she moved to Bristol and became a plumber.
She spent much of her time defending the marginalised and under-privileged, attending anti-fascist rallies, and offering support to the women of Dale Farm when they were threatened with eviction. A vegan and animal lover, she attended hunt sabotages and her name is honoured on PETA's 'Tree of Life' Memorial. Anna went to Rojava in May 2017 with a strong commitment to women's empowerment, full representation of all ethnicities and protection of the environment.
Anna died on March 15, 2018 when she was hit by a Turkish airstrike in the town of Afrin, northern Syria. Anna was fighting with the Women's Protection Forces (YPJ), when she was killed.
Through labor and union organizing, Sopo, Sabrina and Linda are not only fighting for the rights of essential workers, women workers, migrant workers and sex workers, but the rights of all workers.
The fight to end workers’ exploitation is a feminist struggle, and shows us that there are no feminist economies without feminist unions.
This section will guide you on how to ensure your research findings are representative and reliable.
In this section:
- Collect your data
1. Before launch
2. Launch
3. During launch- Prepare your data for analysis
1. Clean your data
2. Code open-ended responses
3. Remove unecessary data
4. Make it safe- Create your topline report
- Analyze your data
1. Statistical programs
2. Suggested points for analysis
If you also plan to collect data from applications sent to grant-making institutions, this is a good time to reach out them.
When collecting this data, consider what type of applications you would like to review. Your research framing will guide you in determining this.
Also, it may be unnecessary to see every application sent to the organization – instead, it will be more useful and efficient to review only eligible applications (regardless of whether they were funded).
You can also ask grant-making institutions to share their data with you.
Your survey has closed and now you have all this information! Now you need to ensure your data is as accurate as possible.
Depending on your sample size and amount of completed surveys, this step can be lengthy. Tapping into a strong pool of detail-oriented staff will speed up the process and ensure greater accuracy at this stage.
Also, along with your surveys, you may have collected data from applications sent to grant-making institutions. Use these same steps to sort that data as well. Do not get discouraged if you cannot compare the two data sets! Funders collect different information from what you collected in the surveys. In your final research report and products, you can analyze and present the datasets (survey versus grant-making institution data) separately.
There are two styles of open-ended responses that require coding.
Questions with open-ended responses
For these questions, you will need to code responses in order to track trends.
Some challenges you will face with this is:
If using more than one staff member to review and code, you will need to ensure consistency of coding. Thus, this is why we recommend limiting your open-ended questions and as specific as possible for open-ended questions you do ask.
For example, if you had the open-ended question “What specific challenges did you face in fundraising this year?” and some common responses cite “lack of staff,” or “economic recession,” you will need to code each of those responses so you can analyze how many participants are responding in a similar way.
For closed-end questions
If you provided the participant with the option of elaborating on their response, you will also need to “up-code” these responses.
For several questions in the survey, you may have offered the option of selecting the category “Other” With “Other” options, it is common to offer a field in which the participant can elaborate.
You will need to “up-code” such responses by either:
Analyze the frequency of the results
For each quantitative question, you can decide whether you should remove the top or bottom 5% or 1% to prevent outliers* from skewing your results. You can also address the skewing effect of outliers by using median average rather than the mean average. Calculate the median by sorting responses in order, and selecting the number in the middle. However, keep in mind that you may still find outlier data useful. It will give you an idea of the range and diversity of your survey participants and you may want to do case studies on the outliers.
* An outlier is a data point that is much bigger or much smaller than the majority of data points. For example, imagine you live in a middle-class neighborhood with one billionaire. You decide that you want to learn what the range of income is for middle-class families in your neighborhood. In order to do so, you must remove the billionaire income from your dataset, as it is an outlier. Otherwise, your mean middle-class income will seem much higher than it really is.
Remove the entire survey for participants who do not fit your target population. Generally you can recognize this by the organizations’ names or through their responses to qualitative questions.
To ensure confidentiality of the information shared by respondents, at this stage you can replace organization names with a new set of ID numbers and save the coding, matching names with IDs in a separate file.
With your team, determine how the coding file and data should be stored and protected.
For example, will all data be stored on a password-protected computer or server that only the research team can access?
A topline report will list every question that was asked in your survey, with the response percentages listed under each question. This presents the collective results of all individual responses.
Tips:
- Consistency is important: the same rules should be applied to every outlier when determining if it should stay or be removed from the dataset.
- For all open (“other”) responses that are up-coded, ensure the coding matches. Appoint a dedicated point person to randomly check codes for consistency and reliability and recode if necessary.
- If possible, try to ensure that you can work at least in a team of two, so that there is always someone to check your work.
Now that your data is clean and sorted, what does it all mean? This is the fun part where you begin to analyze for trends.
Are there prominent types of funders (government versus corporate)? Are there regions that receive more funding? Your data will reveal some interesting information.
Smaller samples (under 150 responses) may be done in-house using an Excel spreadsheet.
Larger samples (above 150 responses) may be done in-house using Excel if your analysis will be limited to tallying overall responses, simple averages or other simple analysis.
If you plan to do more advanced analysis, such as multivariate analysis, then we recommend using statistical software such as SPSS, Stata or R.
NOTE: SPSS and Stata are expensive whereas R is free.
All three types of software require staff knowledge and are not easy to learn quickly.
Try searching for interns or temporary staff from local universities. Many students must learn statistical analysis as part of their coursework and may have free access to SPSS or Stata software through their university. They may also be knowledgeable in R, which is free to download and use.
• 2 - 3 months
• 1 or more research person(s)
• Translator(s), if offering survey in multiple languages
• 1 or more person(s) to assist with publicizing survey to target population
• 1 or more data analysis person(s)
• List of desired advisors: organizations, donors, and activists
• Optional: an incentive prize to persuade people to complete your survey
• Optional: an incentive for your advisors
Survey platforms:
• Survey Monkey
• Survey Gizmo (Converts to SPSS for analysis very easily)
Examples:
• 2011 WITM Global Survey
• Sample of WITM Global Survey
• Sample letter to grantmakers requesting access to databases
Visualising Information for Advocacy:
• Cleaning Data Tools
• Tools to present your data in compelling ways
• Tutorial: Gentle Introduction to Cleaning Data