THE BLOG
04/29/2014 08:19 EDT | Updated 06/29/2014 05:59 EDT

The Left Needs More Argument-Based Policies

The once-buzzword "evidence-based policy" has blossomed into a new progressive ethos.

You've heard it used in town hall Q&A sessions and impassioned social media posts, structured as applause lines and retweet engines designed to shield policy positions from the ideologies that direct them. In Liberal circles specifically, look for the tag to bubble into stump speeches as the ultimate misnomer: who to the left or right could possibly disagree with making policy choices based on rational analysis?

Yet missing from this noble appeal is a simple limitation. Decisions informed by data, accurate and impartial as that data might be, can never point to a single, non-ideological policy conclusion. Nor should they be asked to.

When used in progressive circles, evidence-based presumptions tend to universally manifest as a preference for policies of investment. Yet, though my biases see benefit in pooled public resources managed by elected officials, it is possible to understand an inclination, both for those too wealthy and too impoverished to benefit from the current height of our social safety nets, to cash out of mechanisms they don't perceive as proportionally benefiting them.

We can't lean on "evidence-based policy making" in the same sense that we can't lean on "doing the right thing," hollow in the realization that we could never collectively find even a pedestrian definition of "right" we could all agree on.

Ask supporters of Toronto mayoral candidate Rob Ford if they support evidence-based policy and they'll say yes: eliminating the vehicle registration fee has made it $60 cheaper to operate the car I drive to work, and contracting out waste collection west of Yonge St. will save the city $11 million each year with no impact on service.

Ask supporters of, say, Toronto mayoral candidate Olivia Chow if they support evidence-based policy and they will also say yes: a reinstated vehicle registration fee would be a structurally sensitive $50 million per year revenue tool, and any potential saving from contracting out waste collection is not enough to offset both the symbolic and labour implications of city service privatization.

The waste collection issue in particular illustrates the challenge for those who hold up evidence-based policy as a means to disarm ideological conservatism.

During a televised mayoral debate last month, John Tory brought an expertly framed attack against Olivia Chow, pitting strong evidence for potential cost savings and service improvements by expanding privatization against the ideological counter-argument he knew Chow's pragmatist marching orders wouldn't allow her to make.

Tory's calculation worked.

The result was a grippingly awkward appeal promoting direct competition between publicly and privately-administered social services, a vision of Yonge St. as a sort of West Side Story of policy experiments.

Chow's response needed to be the one thing she couldn't say: sometimes it's not just about the numbers, our decisions can't always be based on the evidence the public deems relevant. It needed to defend the benefits and costs of organized workforces and maintaining public control over public services, each of which she has eloquently championed in tenures past.

Instead, the exchange betrayed what may have solidified as the defining insecurity of Canada's left: it can be easier to defer to pragmatism than it is to argue your convictions.

Perhaps this is why so much time has been spent over the past several years itemizing where Toronto Mayor Rob Ford has been incorrect, instead of arguing for why he's been wrong. In the struggle to correct for labels of fiscal irresponsibility, progressives may have embraced evidence as a stronger dogma than ideology.

What's lost in discourses lauding evidence-based policy is the nagging sense of agency over the policy directions we pursue; the concessions our ideologies are forced to support. Faced with that choice, I'll take argument-based policy every time.

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