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Advocate for gender equality and manage resistance

Activity 3.3

Advocate for gender equality and manage resistance

Aim.

This section outlines some strategies you can use when you encounter resistance to incorporating gender analysis in your work.

Question.

What strategies can I use to address different kinds of resistance?

Understand.

Gender analysis can challenge usual ways of thinking and making policy, and you may sometimes encounter resistance. This resistance can come from within an organization, or from stakeholders outside of your organization. Both women and men may hold negative or dismissive attitudes to gender analysis or have competing perspectives or priorities.

What strategies can I use to address different kinds of resistance?

Gender analysis must be accompanied by the resources to do the job and the support and advocacy of leaders. Proactive, engaged and evidence-based communication can help develop support for gender analysis and reduce bias. More specifically you may come across the following scenarios:

Source: this table is summarized from Gender Toolkit developed by the Office for Women, Queensland, Australia.
Issue Your Response

Decision makers do not believe that gender inequalities exist and are relevant to this policy.

“Gender analysis is not relevant to this policy issue" and therefore, “We do not need to consider women in the context of this policy change”

  • Present sex-disaggregated statistical evidence from your gender analysis
  • Provide examples and case studies from qualitative evidence

Decision makers believe that gender inequalities exist but do not think they are systemic.

“Gender gaps are not caused by access to resources, or biases and discrimination" and therefore “We only need to think about women at relevant points in the policy cycle, not throughout it”

  • Insist that women participate throughout the policy development process
  • Insist on inclusive and diverse representation
  • Use broad evidence to develop gender sensitive outcomes

The person responsible for gender analysis does not support gender analysis.

This person may stall the gender analysis process by not attending meetings, dismissing concerns or avoiding making key decisions.

  • Engage “champions” to help progress the gender analysis
  • Document the gender analysis process
  • Raise issues regularly

Leaders only pay lip service to gender analysis.

Leaders praise attention to gender issues but come up with excuses to avoid committing to action.

  • Engage “champions” at a high level in your organization
  • Embed gender analysis in the policy project rather than including it as an “add-on”
  • Ensure monitoring and evaluation systems in place
  • Set up a project reference group

Leaders give gender analysis work to women’s policy officers to perform, separating it from policy process.

  • Repeatedly make the point that gender issues are important for the health of the whole organization
  • Point out and provide evidence to show that addressing gender inequality has wider benefits for the economy

Leaders give one woman a position on a committee or board to give a “woman’s point of view”.

This is an example of tokenism (a symbolic effort to give the impression of gender equality).

  • Call out tokenism
  • Find allies and build support for the woman and other diversity

Leaders demand more information before taking action.

Leaders suggest a research project when given information about gender inequality or discrimination rather than taking action to address it eg “We don’t know enough about this problem”

  • Agree that we can learn more about an issue, but this does not have to delay acting
  • Give examples of other issues where more research is needed but policy work continues
  • Suggest an initial literature review to summarize the body of available evidence
  • Recommend research that is action-oriented and has delivery and review built into it as part of a pilot phase

Leaders think collecting gender data is too expensive.

Leaders say that collecting sex-disaggregated data will cost too much.

  • Usually, minimal cost in producing gender statistics with existing tools (can be as simple as asking an extra question or adding an extra column)
  • Significant cost only comes from completely new investigations eg surveys

Leaders think data quality will be negatively impacted when data is disaggregated by sex.

  • Tell leaders that including sex-disaggregated data will add value to the whole dataset
  • State that disaggregating data often means data is more accurate as more checks are performed

Case study: Diversity managers can reduce bias in decision making.

Recent studies in reducing the gender pay gap have shown that appointing diversity managers to monitor organizational processes, including monitoring recruitment and promotion processes, can reduce bias in decision making and improve gender accountability.

However, research found to be effective, diversity managers needed to have sufficient authority within an organization. For example,

  • be senior management or executive level
  • have access to and visibility of internal data
  • be in a position to ask for more information regarding decisions
  • be empowered to develop and implement diversity strategies and policy.

Source: https://gender-pay-gap.service.gov.uk/actions-to-close-the-gap/effective-action


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