Transcript Policy making processes - Families and Friends for Drug Law Reform

Evidence-based drug policy –
myth or reality?
Alison Ritter, DPMP Director
NDARC
Presentation 6th Feb, 2007, Canberra
Illicit drug policy
• Drug policy is complicated
• Multiple perspectives
―Users, families, health professionals, police,
politicians, community members
• Strong public opinions
• Significant government spending (*)
• Complicated interventions (*)
Significant government
spending
Total spending:
$3.2 billion p.a.
Direct:
$1.3 billion (41%)
Indirect/consequences $1.9 billion (59%)
Federal Govt:
State/Territory Govt:
30%
70%
Law enforcement
56%
Australian Governments Illicit Drug-related Spending (2002-03)
Health-Related
Consequences
5%
Crime-Related
Consequences
51%
Other consequences
3%
Interdiction
14%
Prevention
22%
Direct drugs
spending
41%
Law enforcement
42%
Treatment
19%
Harm Reduction
2%
Other Policy
1%
Government spending
(direct only)
Law enforcement
$553.9m
($431 to 705)
Interdiction
$181.5m
($149 to 351)
Prevention
$295.8m
($88 to 534)
Treatment
$256.3m
($204 to 279)
Harm reduction
$ 26.3m
($19 to 44)
Complicated responses
• Law enforcement, eg:
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∙
∙
Legalisation of drugs
Crop eradication programs
Customs and border control
Crackdowns and Raids
Police discretion, diversion, drug courts
• Prevention, eg:
∙ Mass media campaigns
∙ School-based drug education
• Treatment, eg:
∙
∙
∙
∙
Detoxification
Methadone or buprenorphine maintenance
Therapeutic communities
Cognitive behavioural relapse prevention
• Harm reduction, eg:
∙ Needle Syringe Programs
∙ Peer education for users
∙ Non-injecting routes of administration
Evidence-based policy?
• Simple question = what works best?
• Research usually limited on this
• Doesn’t take into account dynamic
interactions between sectors
• Doesn’t take into account different
outcomes
• Doesn’t take into account policy making
processes
Policy making processes relationship to evidence?
•
Uptake of evidence in policy-making
Frustration by researchers
Policy-makers feeling misunderstood
•
Problems:
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long (researchers) vs short (policymakers) timeframes;
ambiguity & lack of certainty in much social science research;
inaccessibility of research results
sheer bulk of research materials;
research career structures and the academic reward systems;
lack of clarity about roles (for example balancing objectivity and
advocacy);
rapid change in the policy environment;
problems of governmental capacity;
clash of cultures; and
communication failures between researchers and policy makers
• Solutions?
― summary reports, bulletins, dot points
― personalised briefings
― use of mail outs
― respect the limited time of policy makers
― be patient
― maintain a reputation of objectivity
― think about and prepare ‘good news’ angles to the research
― nurture political champions
― develop mutual understanding and respect
• But even with these, not much progress
• Solution may lie in understanding the policymaking processes better
“The policy world is as alien to most
researchers as a distant foreign land and
most do not even realise it”
Michael Agar, 2002
Models of policy making
•
There is not one model of how policy is
made
•
Researchers usually assume that the
process is linear:
Problem
•
Options
Solutions
And that it is rational!
Implementation
So, models of policy
making…
•
Technical/rational model
•
Incrementalism model
•
Power and pressure groups
•
Interactive model
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Garbage can model
•
Advocacy coalition framework
•
Punctuated equilibrium
•
etc
Rational/technical
approach
• Conventional image: ID an issue, seek
solutions
• Series of steps
1.
2.
3.
4.
5.
6.
identify problem
identify causes
develop options
analyse options
select an intervention
implement and evaluate
• Fundamental, exhaustive, rational, root
approach
Rational/technical model
• Case example: improving
pharmacotherapies - buprenorphine
• Implications for researchers
―Engage in steps 1-4 (ID problems, causes,
options)
―Conduct research that is relevant, timely,
credible
―Know which problems are on the agenda
―Have ready synthesised reports to feed into the
problem, causes or options steps
Incrementalism
• Policy making is not dramatic – rather
small incremental shifts
• Successive limited comparisons between
existing policies (or alternatives)
• Comparing marginal values
• Better than to attempt (and fail) at big
change
Lindblom, C., E. (1959). The science of 'muddling through'. Public Administration Review, 19, 79-88.
Lindblom, C., E. (1979). Still muddling, not yet through. Public Administration Review, 39(26), 517-526.
Incrementalism
• Case example: prevention programs in
schools (education/information competency approach)
• Implications for researchers
―Prepare for long time frame (tobacco 20+yrs)
―Tight simple comparative analyses (within
budget) are highly valued.
“Garbage can” model
• Three independent streams:
― Problems
― Politics
― Policy processes/solutions, alternatives
• Sloshing around, waiting to be matched up
• Policy window opens: task = to match problems
and solutions
Kingdon, T. (2003) Agendas, Alternatives and Public Policies. (2nd Ed). NY: Longman
“Garbage can” model
1. PROBLEMS
Agenda setting
oIndicators and monitoring
oFocusing events
oSymbols
oBudgets
Interpretation
Problem recognition (“should do something”)
oNeed a solution/alternative
Rise and fade
2. POLITICS
Agenda setting
Influenced by:
oNational mood
oOrganised political forces
oGovernmental phenomena
Consensus building through bargaining
Coupling of
1+2+3
Policy
entrepreneurs:
join problem,
solution and
politics
POLICY
WINDOW
Small/short and
scarce.
3. POLICY PROCESSES
Alternatives
Policy community
Ideas as an evolutionary processes (mutation & recombination)
Criteria for success of an alternative (technical feasibility;
values congruence; constraints manageable; public and political
acceptability)
Softening up (years)
Emerging consensus (diffusion & tipping point)
Predictable or
Unpredictable
“Problem”
window (1)
“Politics”
window (2)
Kingdon, T. (2003) Agendas, Alternatives and Public Policies. (2nd Ed) NY: Longman
“Garbage can” model
• Case example: NCADA: problem = IDU
and/or AIDS; politics = Hawke; policy
processes/solutions = various (academics,
drug treatment community, gay
community).
• Implications for researchers
―“Policy processes” component – key role in
presenting alternatives (and data on problems)
―Look for when policy windows open
―Match up problems and solutions creatively
(don’t pair too early)
Power & pressure
groups
• Three forces that determine policy:
―Ideology (philosophy, values)
―Interests (primarily self-interests)
―Information (multiple sources…)
• The distribution of power determines
whose I-I-I will be dominant.
Weiss, C. H. (1983). Ideology, interests and information: the basis of policy positions. In D. Callahan &
B. Jennings (Eds.), Ethics, Social Sciences and Policy Analysis. NY: Plenum Press.
Power & pressure
groups
• Case example: Diversion initiative
―Different constructions of the problem.
Different Ideology, Interests and Information.
• Implications for researchers
―“Information” component
―Be aware of all “information” types and
influences
―Strategic dissemination: mailouts, briefings
etc.
Advocacy Coalition
Framework
• Policy subsystem = interaction of diverse actors
interested in same policy area.
• Illicit drugs as a policy subsystem.
• Within each policy subsystem, advocacy coalitions
form (because diversity of views across the whole
subsystem). Usually 2-4 AC’s.
• AC’s include: policy analysts, academics,
journalists, advocates etc.
• Policy change occurs when AC’s are in conflict and
one AC rises to ‘power’ – specifies the agenda,
and the policies
Sabatier, P. A. (1988). An advocacy coalition framework of policy change and the role of policy-oriented learning therein.
Policy Sciences, 21, 129-168.
Advocacy Coalition
Framework
• Case example: Supervised Injecting
Centre (Van Beek, 2004)
― Players = local community, A&D service providers, local
chamber of commerce, the churches, non-govt expert bodies,
parliamentary processes, media, advocates.
• Implications for researchers
―Know the AC’s that exist
―Provide briefings etc for significant players
―Stakeholder engagement in the research from
the start
―Use advocacy strategies
Summary
• Different models apply at different times
• Models overlap – they describe/focus on
different components of the same
processes
• No one way to ensure uptake of evidence
Don’t despair..
• Role of evidence – in above models have mainly
been looking at research as “instrumental” to a
direct policy decision.
― Knowledge-driven (new science)
― Problem-solving (to answer a policy question)
• But other ways in which research evidence is
used:
― Interactive (iteration among multiple players)
― Political (to support a position; “ammunition”)
― Tactical (to delay, deflect criticism, show responsibility)
― Enlightenment (new ideas permeate over time, “backdrop of
ideas”) *
Where to from here?
DPMP aims to
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develop the evidence-base for policy;
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develop, implementing and evaluating dynamic policyrelevant models of drug issues; and
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study policy-making processes in Australia
Challenges
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Further work on models and what they mean for drug
policy
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Comparisons of policy options
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Policy analysis rather than descriptive research
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Improving the evidence AND the intersection between
researchers and decision-makers
Acknowledgements
This work forms part of the Drug Policy Modelling
Program (DPMP). Funded by:
― Colonial Foundation Trust
― NHMRC Career Development Award
Thanks to:
• The DSS study group (at the ANU, led by Prof
Bammer)
• RegNet, the ANU
Further information
Assoc Prof Alison Ritter
Drug Policy Modelling Program, Director
National Drug and Alcohol Research Centre
UNSW, Sydney, NSW, 2052, Australia
E: [email protected]
T: + 61 (2) 9385 0236
DPMP Monographs:
http://notes.med.unsw.edu.au/ndarcweb.nsf
Research – current – Drug Policy Modelling Program