Presence of Opportunities for Cultural Participation

Measuring the number of non-profit cultural organizations.

This indicator measures the number of non profit cultural organizations present in Santa Monica.Explore the data
organizations
Current
52organizations
Dec 2020 Target
Goal Period ended December 2020

            What is this indicator?

            This indicator measures the number of non-profit cultural organizations in Santa Monica.

            Why is it important?

            Santa Monica’s residents show extraordinarily high levels of personal participation in cultural activities and an expansive understanding of their role in a community. The number of non-profit cultural organizations, who are the primary providers of cultural services, is one of the ways to illustrate the level of opportunity to get involved with cultural activities throughout the city.

            How are we doing?

            As of 2013, there were 52 non-profit cultural organizations in Santa Monica. The city’s arts and cultural organizations serve an annual audience of at least 278,000 and 44% of that attendance is free .More than eight of ten organizations provide arts education in schools or after school. The high cost of real estate and the associated pressure that this puts on non-profit organizations resulted in the loss of two Santa Monica core arts agencies in 2015.

            Pr ogress is needed for greater coordination and cooperation among arts and cultural organizations, and among artists. Despite Santa Monica’s small size, the professional arts community tends to function in some degree of isolation and nearly all would welcome efforts to convene and coordinate.

            How can we help?

            • Support local artists and creative sector businesses.
            • Get involved with local arts events and festivals by following the Cultural Affairs Division and the Santa Monica Arts Foundation .

      Data Governance

      describes the quality of the data itself. Governance issues generally indicate that the data source is considered incomplete or unreliable.

      Model Health

      describes the quality of the predictive model. If the model health is poor, the trend prediction should not be trusted.

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