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Educational Policy Analysis
& Program Evaluation.

From framing a policy problem to weighing options, allocating scarce resources, and judging effects and equity. A rigorous, interactive guide to the disciplined analysis that turns evidence into decisions — built for graduate students, evaluators, and educational leaders who must act under real constraints.

Build a logic model Weigh a policy's options

Stages of the policy cycle

Decision-analysis strands

Logic-model stages

Policy criteria

Memorandum

To Educational leaders, researchers & decision-makers

From Freddrick Logan — Technologist & Education

Date 2026

Re Educational Policy Analysis & Program Evaluation

Policy analysis reasons toward a defensible choice before we act; program evaluation judges what that choice actually accomplished, for whom, and at what cost.

The policy cycle — problem definition through evaluation and change — gives a spine for locating a decision and the analysis it needs, while implementation is where many reforms are quietly lost.
A logic model makes a program's theory of change explicit, tracing inputs to activities to outputs to outcomes to impact — and exposing the difference between merely doing and actually changing.
Options are weighed against five criteria — effectiveness, efficiency, equity, feasibility, and political acceptability — whose trade-offs are the point, not a nuisance to be hidden.
Efficiency is worked through cost-effectiveness and cost-benefit analysis, disciplined by discounting and opportunity cost rather than arithmetic alone.
An equity lens disaggregates every result and asks who benefited and who was left out — reframing merit and worth around justice, not just the average effect.
The analysis earns its keep only when it is communicated in a decision memo a busy leader can follow, act on, and own with open eyes.

Orientation

Two crafts, one discipline of judgment

Policy analysis asks which course of action best serves a public purpose before we act; program evaluation asks whether what we did actually worked, for whom, and at what cost after we act. Together they form a continuous loop of reasoned decision-making under uncertainty.

Policy analysis — reasoning toward a choice

Defines a problem and clarifies whose problem it is
Constructs and compares realistic alternatives
Projects outcomes and confronts trade-offs explicitly
Applies criteria — effectiveness, efficiency, equity, feasibility
Recommends a defensible course of action, with candor about limits

Program evaluation — judging merit and worth

Assesses whether a program is well-designed and implemented
Measures outcomes against a theory of change
Attributes effects with appropriate design and comparison
Weighs cost against benefit and disaggregates by group
Feeds credible findings back into decision and improvement

The analyst's stance — neither advocate nor technician. Good analysis is transparent about assumptions and values, honest about what the evidence can and cannot bear, and useful to a decision-maker who must choose among imperfect options.

The policy process

The stages of the policy cycle

The stages heuristic (Lasswell, Jones, Anderson) frames policymaking as a cycle. Real politics is messier and iterative — but the stages give you a spine for locating where a decision sits and what analysis it needs.

Problem definition

Name the condition, establish that it is a public problem, and frame it. How a problem is defined largely determines which solutions become thinkable.

Agenda setting

The problem competes for scarce attention among policymakers and the public. Focusing events, framing, and problem/politics/policy streams (Kingdon) open a window.

Policy formulation

Alternatives are designed and analyzed — instruments, mandates, incentives, capacity-building — and their likely consequences projected and compared.

Adoption / legitimation

An option is authorized through legislative, regulatory, or administrative choice, acquiring legitimacy and the resources to proceed.

Implementation

The policy is enacted by agencies, schools, and street-level actors whose discretion shapes what the policy actually becomes on the ground.

Evaluation & change

Effects, costs, and equity are assessed; findings feed back into maintenance, revision, or termination — and the cycle begins again.

Implementation is not a formality. Pressman & Wildavsky showed that the gap between a policy's promise and its delivery is where many reforms are lost — a "complexity of joint action" across many hands, each of whom can slow or reshape it.

Decision Analysis I–IV

A graduate arc in systematic inquiry

The disciplined study of decisions builds in four movements — from the logic of inquiry itself, through quantitative and qualitative evidence, to the applied craft of program analysis and policy evaluation. Select a strand to see its purpose, core tools, and the questions it answers.

I — The logic of systematic inquiry

Establishes how we come to warranted knowledge for decisions: research questions, concepts and their measurement, the difference between association and cause, validity of inference, and the ethics of studying people. It is the grammar the later strands speak.

Central question: "How do we reason from evidence to a defensible claim we can act on?"

Shadish, Cook & CampbellKing, Keohane & VerbaPopper

FocusDesign of inquiry & inference
Key ideasValidity, causation, measurement, ethics
DistinctionsInternal / external / construct validity
SkillFraming answerable, decision-relevant questions
OutputA coherent research / evaluation design

II — Quantitative analysis

Turns numbers into evidence about scope, difference, and effect: descriptive statistics, sampling and inference, regression, and the design logic behind experiments and quasi-experiments used to estimate causal effects of programs and policies.

Central question: "How much, how many, and does the difference we see exceed chance and rival explanations?"

Angrist & PischkeMurnane & WillettCook & Campbell

DataMeasured variables, administrative & survey data
ToolsRegression, hypothesis tests, effect sizes
Causal designsRCT, difference-in-differences, RD, IV
StrengthScope, precision, generalization
OutputEstimated effects with uncertainty

III — Qualitative analysis

Explains how and why a policy plays out as it does. Through interviews, observation, and documents it recovers meaning, mechanism, and context — indispensable for understanding implementation, unintended consequences, and the experience of those a policy touches.

Central question: "What is actually happening here, how do people make sense of it, and through what mechanisms?"

Miles, Huberman & SaldañaYinLipsky (street-level)

DataInterviews, observation, documents, cases
ToolsCoding, thematic & case analysis, process tracing
StrengthMeaning, mechanism, implementation detail
ComplementsExplains the "why" behind quantitative effects
OutputContextual, mechanism-rich explanation

IV — Program analysis & policy evaluation

Integrates the prior strands into applied practice: articulating a program's theory of change, framing evaluation questions, choosing a design fit for the decision, appraising costs and benefits, and judging merit, worth, and equity to inform a real choice.

Central question: "Did this program work — for whom, at what cost, and what should we do next?"

Rossi, Lipsey & FreemanStufflebeamPattonBardach

FocusApplied evaluation & policy recommendation
ToolsLogic models, CIPP, cost-benefit, criteria
ModesFormative, summative, developmental
StandardUtility, feasibility, propriety, accuracy
OutputA defensible judgment & recommendation

Signature interactive · Logic Model Builder

Build a program's theory of change

A logic model is the backbone of evaluation: it makes explicit how resources become activities, activities become results, and results — if the theory holds — become impact. Step through building one for a sample after-school peer tutoring initiative, then read any stage for its definition.

Sample program — Peer Tutoring Initiative: trained older students tutor struggling 9th-graders in reading and math twice weekly.

Inputs

Activities

Outputs

Outcomes (S/M/L)

Impact

Click any stage above, or walk through the chain one link at a time.

Read left to right

The "if–then" chain

Each stage is linked by an implicit "if we invest these inputs, then we can run these activities; if these activities produce these outputs, then these outcomes should follow." Naming the links exposes where a theory of change can break.

Outputs ≠ outcomes

Doing vs. changing

Outputs count what the program produced (sessions held, students served). Outcomes capture change in participants (skills, behavior, achievement). Confusing the two is the most common evaluation error.

Assumptions & context

What must hold true

Every model rests on assumptions (tutors attend, matches are stable) and external factors (home support, school climate). Surfacing them tells you what to monitor and what could confound your results.

Provenance — the logic-model form is codified in the W.K. Kellogg Foundation Logic Model Development Guide and the University of Wisconsin–Extension logic model, and underlies theory-based and outcomes evaluation across the field.

Evaluation frameworks

Choosing a lens for the judgment

No single framework fits every evaluation. Each answers a different question and enters the program's life at a different moment. Match the framework to your purpose and your stage.

Framework	Core question	Structure	Best used for
Formative	How can we improve it while it runs?	Ongoing feedback during design/delivery	Refining a program in progress
Summative	Did it work; should it continue?	Judgment of outcomes after maturity	Accountability, continuation, scaling decisions
CIPP (Stufflebeam)	Is the program well-conceived and run?	Context · Input · Process · Product	Comprehensive, improvement-oriented evaluation
Kirkpatrick's four levels	Did training change behavior & results?	Reaction · Learning · Behavior · Results	Training & professional-development programs
Theory-based / outcomes	Do outcomes follow the change theory?	Logic model / theory of change tested	Explaining why a program does or doesn't work
Needs assessment	What is the gap we should address?	Gap between current & desired state	Front-end planning before a program exists
Utilization-focused (Patton)	Will intended users actually use it?	Designed around specific users & uses	Ensuring findings inform real decisions
Developmental (Patton)	How do we adapt as the program evolves?	Real-time feedback amid emergence & complexity	Innovations and systems change without a fixed model
Empowerment (Fetterman)	Can stakeholders evaluate themselves?	Participants own the evaluation & build capacity	Community programs; self-determination & ownership
Goal-free (Scriven)	What did it actually do — intended or not?	Evaluator brackets stated goals; looks at all effects	Surfacing side effects and unintended consequences
RE-AIM	Will it work at scale in the real world?	Reach · Effectiveness · Adoption · Implementation · Maintenance	Judging external validity and scalability of an intervention

CIPP · Context

Needs & goals

Assess needs, assets, and problems in the setting to set defensible goals and priorities.

CIPP · Input

Plans & resources

Appraise competing strategies, work plans, and budgets for feasibility and fit.

CIPP · Process

Implementation

Monitor how faithfully and how well the plan is being carried out in practice.

CIPP · Product

Results

Measure and interpret outcomes — intended and unintended, short and long term.

Policy analysis criteria

The standards by which options are weighed

Bardach's "eightfold path" ends by projecting outcomes and confronting trade-offs. These five criteria are the yardsticks analysts apply — rarely satisfied all at once, which is precisely why the trade-offs must be made explicit rather than hidden.

Effectiveness

Does it work?

The extent to which the option actually achieves the intended goal or reduces the problem.

Efficiency

At what cost?

Benefits relative to costs — cost-benefit (dollar-valued) or cost-effectiveness (cost per unit of outcome).

Equity

For whom?

How burdens and benefits are distributed across groups — fairness, not just aggregate gain.

Feasibility

Can it be done?

Administrative, technical, and fiscal capacity to actually implement the option as designed.

Political acceptability

Will it be adopted and sustained?

Whether relevant stakeholders and authorizers will tolerate or support the option — the criterion that determines whether a technically sound policy ever survives contact with politics.

Weigh the options — check each criterion this policy option credibly meets

Effectiveness — evidence it achieves the goalThere is credible evidence (from theory, pilots, or comparable programs) that the option meaningfully reduces the problem.

Efficiency — benefits justify the costsA cost-benefit or cost-effectiveness comparison shows the option is a defensible use of scarce resources.

Equity — fair distribution of burdens & benefitsThe option narrows rather than widens gaps, and its effects have been disaggregated by group.

Feasibility — capacity to implementThe administrative, technical, and fiscal capacity exists to deliver the option as designed.

Political acceptability — authorizers will support itKey stakeholders and decision-makers will adopt and sustain the option through the political process.

Composite option strength

Check the criteria this option meets

Trade-offs are the point. The most efficient option is often not the most equitable; the most effective is often not the most feasible or politically acceptable. Analysis does not eliminate these tensions — it makes them visible so the decision-maker owns them consciously.

Resource allocation & accountability

Turning dollars into learning

Policy is enacted through budgets. How resources are raised, deployed, and accounted for expresses a system's real priorities — and whether stated commitments to equity survive the ledger.

Budgeting logic & resource deployment

Adequacy — are resources sufficient to reach the standard expected of all students?
Equity vs. equality — equal spending is not equal opportunity; adequacy often requires unequal, need-weighted allocation
Weighted-student / formula funding — dollars follow students, weighted for poverty, disability, and language needs
Vertical vs. horizontal equity — treating unequal needs unequally vs. equals equally
Cost-effectiveness in deployment — which uses of the marginal dollar move outcomes most (Levin & McEwan)

Accountability systems & assessment

Standards & assessment — clear goals with valid, reliable measures of student learning
Consequential accountability — attaching stakes to results, and its incentive effects (Campbell's Law, narrowing)
Inputs, outputs, outcomes — accountability should reach outcomes, not just compliance with inputs
Data use & continuous improvement — evidence cycles that inform practice, not just rank it
Transparency & reporting — disaggregated public reporting that surfaces gaps rather than masking them

Campbell's Law. "The more any quantitative indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the processes it is intended to monitor." A caution at the heart of high-stakes accountability design.

Foundations of systemic (in)equity

The equity lens on policy and evaluation

An aggregate "it works" can conceal that a policy worked for some and failed others — or widened the very gaps it meant to close. An equity lens is not an add-on; it changes what counts as success.

Structural inequity

Beyond individual bias

Inequities are produced and reproduced by policies, funding structures, and institutional routines — not only individual attitudes. Analysis must interrogate the system, not just the actor.

Disaggregation

Averages hide gaps

Break every result down by race, income, disability, language, and gender. An improved mean can mask a widening disparity beneath it.

Equity vs. equality

Same ≠ fair

Equality gives everyone the same; equity gives each what they need to reach a common standard. Adequacy and vertical equity operationalize the difference.

Unintended consequences

Watch the second-order effects

Policies ripple. Incentives get gamed, resources shift, and burdens fall unevenly. Evaluate for the effects you didn't intend, not only the ones you promised.

Equity-focused evaluation asks not just "what was the average effect?" but "who benefited, who was left out, and did the intervention shift the underlying structure of opportunity?" — reframing merit and worth around justice.

A practical method

Bardach's eightfold path to policy analysis

Eugene Bardach's widely taught sequence gives a repeatable spine for an analysis — iterative in practice, but disciplined in structure.

Define the problem

State it as a deficit or opportunity, quantified where possible, framed to admit real solutions — and beware defining the solution into the problem.

Assemble the evidence

Gather data and prior research that bear on the problem's magnitude and on what has worked elsewhere. Spend effort where it changes the answer.

Construct the alternatives

Lay out a realistic menu of policy options — including the status quo as a baseline — before narrowing.

Select the criteria

Choose the evaluative standards — effectiveness, efficiency, equity, feasibility, acceptability — that will discipline the comparison.

Project the outcomes

For each alternative, forecast what would actually happen against each criterion — the hardest and most honest step.

Confront the trade-offs

Where no option dominates, make the trade-offs across criteria explicit and comparable.

Decide

Apply judgment to reach a recommendation — and test it by being able to defend it to a skeptic.

Tell your story

Communicate the analysis clearly to the decision-maker — the "New York taxi driver" test of coherence and candor.

Policy instruments

The tools a government actually has

A policy goal is inert until it is attached to an instrument — a mechanism through which the state acts on behavior. Christopher Hood's Tools of Government sorts them by the resource they draw on (the NATO scheme); Vedung's shorthand calls them carrots, sticks, and sermons. Most real policies bundle several. Naming the instrument disciplines the analysis of feasibility and side effects.

Treasure · Carrots

Incentives

Money that rewards or penalizes: grants, per-pupil funding weights, performance bonuses, vouchers, tax credits. Powerful but costly, and prone to gaming when tied to a single indicator.

Authority · Sticks

Regulation

Legal command: mandates, standards, licensure, class-size caps, accountability sanctions. Fast to enact and low-cost to the treasury, but blunt and dependent on monitoring and compliance.

Nodality · Sermons

Information

Persuasion and disclosure: report cards, public data, awareness campaigns, best-practice guidance, nudges. Cheap and light-touch, but weak where interests or capacity block a response.

Organization · Capacity

Direct provision & capacity

The state acts through its own people and organizations: running schools, deploying coaches, building data systems, and training the workforce that any reform ultimately depends on.

Choosing an instrument is a values choice. The same goal — raise reading scores — can be pursued by paying (incentive), requiring (regulation), publishing (information), or staffing (capacity). Each distributes burdens differently, demands different administrative capacity, and fails in a different way. The instrument, not just the aim, is what the analyst must defend.

Efficiency, worked

Cost-benefit vs. cost-effectiveness

Both ask whether an option is worth its cost, but they answer differently. Cost-effectiveness (CEA) compares cost per unit of a single outcome, so outcomes need not be dollar-valued. Cost-benefit (CBA) converts every effect to money, allowing a net-benefit verdict and comparison across unlike programs. Work a small example (Levin & McEwan's method) to see how each reads the same two programs.

Program	Cost / student·yr	Effect (reading)	CEA: cost per 0.10 SD	CBA: benefit @ $3,000 per 0.10 SD	Net benefit · B/C
A — Class-size reduction	$2,400	+0.15 SD	$2,400 ÷ 1.5 = $1,600	1.5 × $3,000 = $4,500	$4,500 − $2,400 = +$2,100 · 1.9
B — Peer tutoring	$600	+0.20 SD	$600 ÷ 2.0 = $300	2.0 × $3,000 = $6,000	$6,000 − $600 = +$5,400 · 10.0

Reading the result

Same data, converging verdict

CEA says Program B buys a 0.10 SD gain for $300 versus $1,600 for A — roughly five times more outcome per dollar, with no need to price learning. CBA goes further: both clear their cost (net benefits are positive), but B returns $10 per $1 spent against A's $1.90. When outcomes can be credibly monetized, CBA ranks unlike options; when they cannot, CEA still discriminates cleanly.

Discounting & opportunity cost

Why timing and the road not taken matter

Discounting — benefits arrive in the future and must be valued in today's terms: present value = future value ÷ (1 + r)^t. A $10,000 lifetime-earnings gain realized in 10 years, discounted at 3%, is worth only $10,000 ÷ 1.03¹⁰ ≈ $7,441 now. Opportunity cost — every dollar spent on A is a dollar not spent on its best alternative use: the $2,400 for one class-size slot could instead fund four tutoring slots. Cost is what you give up, not just what you write a check for.

The numbers above are illustrative. Real analyses must justify the effect sizes, the shadow price placed on an SD of achievement, the discount rate, and whose costs and benefits count (the standing question). The discipline is not the arithmetic — it is defending every assumption the arithmetic rests on.

Stakeholder analysis

Mapping who can shape the outcome

Feasibility and political acceptability are not abstractions — they are people with power and interests. A power/interest grid (Eden & Ackermann; Mendelow) sorts stakeholders into four quadrants, each implying a different engagement strategy. The point is to anticipate resistance and coalition before, not after, a decision.

High power · High interest

Manage closely — key players

School board, superintendent, teachers' union, state education agency. They can make or break adoption and care intensely. Engage directly, negotiate, and secure their buy-in first.

High power · Low interest

Keep satisfied

Legislature, major funders, taxpayer groups. Able to intervene decisively if roused, but not currently focused. Keep them informed enough that the policy never becomes a surprise grievance.

Low power · High interest

Keep informed — mobilize

Parents, students, front-line teachers, community organizations. Deeply affected but individually weak; consult them, honor their voice, and recognize they can become powerful once organized.

Low power · Low interest

Monitor

Vendors, peripheral agencies, the general public. Low effort for now, but watch for shifts — a focusing event can move a group into a higher-stakes quadrant overnight.

Read the grid dynamically. Positions are not fixed: framing, focusing events, and organizing move stakeholders between quadrants. A good analyst maps the board as it is and as a decision could reshape it — including whose interests the policy itself will strengthen or weaken.

From logic model to theory of change

The map and the explanation

The terms are used loosely, but the distinction is real and useful. A logic model is the operational map — the linear inputs → activities → outputs → outcomes → impact chain (which you built above). A theory of change is the causal argument behind it — why each link should hold, what preconditions must be in place, and what assumptions the whole edifice rests on (Weiss, 1995).

Logic model

What the program does

Linear and left-to-right: resources to results
Describes the components at a glance
Strong for planning, management, and reporting
Built forward from what you have
Best when the pathway is well-understood and stable

Theory of change

Why it should work

Causal and often non-linear, with feedback loops
Names preconditions, assumptions, and rival pathways
Strong for strategy, complexity, and contested change
Built backward from the long-term goal
Best when the pathway is uncertain or systemic

When to use each. Use a logic model to communicate and manage a defined program; use a theory of change to reason about how and why change happens when the terrain is complex, the actors many, and the causal links open to dispute. In practice a theory of change often contains a logic model — the map nested inside the argument.

Implementation & evaluation

Why good designs still fail on the ground

A policy is only as good as its delivery. Implementation science studies the gap between a program on paper and the program students actually receive — and gives evaluators the constructs to measure it (Durlak & DuPre; Dane & Schneider). Without them, a null result cannot distinguish a bad idea from a good idea poorly delivered.

Fidelity

Delivered as designed?

The degree to which the program is carried out as its model intends — the core components present and adhered to. Low fidelity confounds every outcome claim.

Dosage

How much was received?

The quantity actually delivered and taken up — sessions attended, hours engaged. A treatment nobody received cannot show an effect; measure exposure, not just offer.

Reach · Quality · Adaptation

Who, how well, changed how?

Which of the intended population were engaged, how well delivery was executed, and what local adaptations were made — the difference between a faithful variant and program drift.

Formative → summative is a continuum, not a switch. Early on, implementation and process data feed formative judgments that improve delivery; as the program matures and fidelity stabilizes, attention shifts to summative judgments of outcome, cost, and worth. Judging outcomes before implementation is sound is a category error — you would be evaluating a program that was never really delivered.

Equity impact assessment — tick each safeguard your analysis has built in

Disaggregated by subgroupOutcomes will be broken out by race, income, disability, language, and gender — not reported only as an average.

Affected communities engagedThose the policy touches helped shape the problem definition and the design, not merely receive it.

Baseline disparities documentedExisting gaps are measured up front, so "improvement" can be judged against who started where.

Distributional effects assessedThe analysis names who bears the burdens and who reaps the benefits, not just the aggregate gain.

Resources weighted to needAllocation reflects vertical equity and adequacy — more where the need is greater, not identical shares.

Barriers to access addressedPractical obstacles (cost, transport, language, information) that would exclude the intended beneficiaries are anticipated.

Unintended consequences monitoredSecond-order and gaming effects that could fall unevenly are tracked, not only the promised outcomes.

Accountability for gaps assignedSomeone owns closing the disparity, with a plan to act if the policy widens rather than narrows it.

Equity robustness of the analysis

Tick each safeguard your analysis has addressed

Communicating the analysis

Writing the policy memo

Bardach's eighth step — "tell your story" — usually takes the form of a decision memo. Analysis that a busy decision-maker cannot follow does not get used. The memo is a genre with a reliable spine: lead with the recommendation, show the reasoning, and be candid about what you don't know.

Structure

The seven parts of a decision memo

Bottom line up front — the recommendation, in the first lines
Problem statement — what's at stake, quantified, and why now
Background — only the context needed to judge the choice
Alternatives — the realistic options, including the status quo
Criteria & assessment — how each option scores, trade-offs named
Recommendation — the defended choice and its rationale
Risks & next steps — limits, uncertainties, and what to do Monday

Craft

What separates a used memo from a filed one

Lead with the answer; the reader may stop after paragraph one
One page where one page will do; an appendix carries the detail
Show the trade-offs — a memo with no downside is not believed
Quantify claims and cite the evidence behind each number
Write for the decision-maker's world, not the analyst's
Pass the "taxi driver" test: could a smart non-expert follow it?

Candor is persuasive. Naming the weakest link in your own recommendation builds the credibility that makes the rest of it trusted. The goal is not to win an argument but to equip a decision-maker to own a choice with open eyes.

Reference

Core vocabulary

Theory of change — the causal logic by which a program's activities are expected to produce outcomes.
Logic model — the inputs → activities → outputs → outcomes → impact map of that theory.
Formative vs. summative — evaluation to improve vs. evaluation to judge.
Counterfactual — what would have happened absent the program; the basis of causal claims.
Cost-effectiveness — cost per unit of outcome, allowing comparison without dollar-valuing outcomes.

Cost-benefit analysis — comparing costs and benefits expressed in common (dollar) terms.
Adequacy — resources sufficient for all students to meet a defined standard.
Vertical equity — treating students with different needs differently, on purpose.
Implementation fidelity — the degree to which a program is delivered as designed.
Disaggregation — separating results by subgroup to reveal distributional effects.

Foundational scholars & further reading

Bardach — A Practical Guide for Policy Analysis (The Eightfold Path) Weimer & Vining — Policy Analysis: Concepts & Practice Rossi, Lipsey & Freeman — Evaluation: A Systematic Approach Stufflebeam & Shinkfield — Evaluation Theory, Models & Applications (CIPP) Kirkpatrick — Evaluating Training Programs Patton — Utilization-Focused Evaluation Kingdon — Agendas, Alternatives & Public Policies Pressman & Wildavsky — Implementation W.K. Kellogg Foundation — Logic Model Development Guide Levin & McEwan — Cost-Effectiveness Analysis Stone — Policy Paradox: The Art of Political Decision Making McDavid & Hawthorn — Program Evaluation & Performance Measurement Hood & Margetts — The Tools of Government in the Digital Age Bemelmans-Videc, Rist & Vedung — Carrots, Sticks & Sermons Weiss — Nothing as Practical as Good Theory (Theory of Change)