May 16, 2009

API* Heritage Post #16: Solidarity and Disaggregation of Data

This year, in an actual attempt to really observe API* Heritage Month, I'm trying to put up a post a day about what that means to me. Click the tag for API* Heritage to get the whole series.

Often with API* activists and advocates, we speak about common experiences where there may not be many - our discussions of solidarity are really that: not shared histories but analogies of struggle that we can bring to bear in whatever work we're trying to do together now. It's not that our people have the same histories and therefore our struggles are the same: it's that in the stories of the Manongs from the I-Hotel, there are themes and experiences that we can learn from, examples that we can use to build for the future.

Where we go wrong is when we overlook the differences, the uniqueness of Asian and other immigrant community experiences and try to create some kind of meta-narrative where there is none. Vast and discriminatory backlogs in visa processing affect many Asian communities, and offer an opportunity for common stories that bind, but the plight of Filipino American veterans, JA internees, Cambodian deportees, Thai sweatshop workers, and Bhutanese refugees are different from one another.

We, the privileged, can and should find ways to weave stories together to tell stories that are more complex than the 30-second elevator speech: we must find ways to build stories with layers and branching examples that build a narrative (even if it is non-linear) that better captures the multiplicity of experience rather than the simple reduction of this diversity into general bullet points.

While it will not be easy, if we don't do this, we definitely can't rely on the outside world to even begin to understand these complexities, nor to adequately capture the differences. People generally agree that there are big concerns with aggregation of data about our communities into "Asian" or "Other" without data about individual groups. Getting disaggregated data (quantitative and qualitative) is just step one; step two is making sense of that data, then reconfigure and arrange it to both emphasize unique communities and experiences and to find themes and patterns that can facilitate understanding, solidarity, and joint action for shared concerns.

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