Appendix F: Templates and Worksheets
How to Use This Appendix: Each template is designed to be printed or copied for use in class exercises, campaign internships, or professional analytical work. Fill in each field as completely as possible. Partially completed templates are useful for identifying what information is missing from a published poll or political report. Many of these templates double as grading rubrics for the exercises in this textbook.
Template 1: Poll Evaluation Checklist
Based on AAPOR Transparency Initiative Standards and Chapter 10
Use this checklist to evaluate any published poll. Check each box only when you can verify the criterion from available documentation. If information is not publicly disclosed, note that in the "Notes" column — non-disclosure is itself a methodological red flag.
Poll Being Evaluated: ___________
Evaluator Name/Date: ___________
Source of Poll: ___________
Section A: Basic Disclosure (Required for any credible poll)
| # | Criterion | Met? | Notes |
|---|---|---|---|
| 1 | Sponsoring organization(s) are fully identified | ☐ Yes ☐ No ☐ Not disclosed | |
| 2 | The polling firm/methodology provider is identified | ☐ Yes ☐ No ☐ Not disclosed | |
| 3 | Exact question wording is reported verbatim | ☐ Yes ☐ No ☐ Not disclosed | |
| 4 | Question order in the instrument is reported | ☐ Yes ☐ No ☐ Not disclosed | |
| 5 | Field dates (when interviewing was conducted) are reported | ☐ Yes ☐ No ☐ Not disclosed | |
| 6 | Sample size (N) is reported | ☐ Yes ☐ No ☐ Not disclosed | |
| 7 | Margin of error is reported | ☐ Yes ☐ No ☐ Not disclosed | |
| 8 | The population being surveyed is defined (registered voters, likely voters, adults, etc.) | ☐ Yes ☐ No ☐ Not disclosed |
Section B: Methodology Quality
| # | Criterion | Met? | Notes |
|---|---|---|---|
| 9 | Survey mode is identified (telephone RDD, online panel, text-to-web, etc.) | ☐ Yes ☐ No ☐ Not disclosed | |
| 10 | If telephone poll: both landline and cell phone included? Cell phone % reported? | ☐ Yes ☐ No ☐ N/A | |
| 11 | If online poll: panel vendor identified and panel methodology described? | ☐ Yes ☐ No ☐ N/A | |
| 12 | Response rate or completion rate is reported | ☐ Yes ☐ No ☐ Not disclosed | |
| 13 | Weighting variables and targets are disclosed | ☐ Yes ☐ No ☐ Not disclosed | |
| 14 | Likely voter screen methodology is disclosed (if LV results reported) | ☐ Yes ☐ No ☐ N/A |
Section C: Question Quality
| # | Criterion | Met? | Notes |
|---|---|---|---|
| 15 | Questions are neutral (no loaded language, false premises, or leading wording) | ☐ Yes ☐ No ☐ Partially | |
| 16 | Ballot test question uses correct candidate names/offices | ☐ Yes ☐ No ☐ N/A | |
| 17 | Response options are balanced and exhaustive | ☐ Yes ☐ No ☐ Partially | |
| 18 | "Don't know / No opinion" option is offered appropriately | ☐ Yes ☐ No ☐ Partially |
Section D: Reporting Quality
| # | Criterion | Met? | Notes |
|---|---|---|---|
| 19 | Reported results are consistent with disclosed sample sizes and MoE | ☐ Yes ☐ No ☐ Cannot verify | |
| 20 | Topline results available for independent review (topline document linked or published) | ☐ Yes ☐ No ☐ Not disclosed |
Section E: Red Flags (Check any that apply)
- ☐ Sponsor is a political campaign, party, or advocacy organization with an obvious stake in the result
- ☐ Results were released to media before the full topline was published
- ☐ Only favorable subgroup results were highlighted
- ☐ The margin of error is not applied to the differences being discussed
- ☐ Results are described as statistically significant when differences are within the MoE
- ☐ The poll was conducted more than 3 weeks before the reported date
- ☐ Sample size is below 400 (reducing reliability substantially)
- ☐ The firm has a documented history of house effects favoring a particular party
Summary Evaluation
Total criteria met (Sections A–D): _____ / 20
Red flags identified: _____
Overall credibility rating: - ☐ High (17–20 criteria met, 0–1 red flags): Poll meets professional standards; results can be used with appropriate uncertainty - ☐ Moderate (12–16 criteria met, 2–3 red flags): Important information missing; treat results with caution; do not treat as definitive - ☐ Low (fewer than 12 criteria met, or 4+ red flags): Significant methodological concerns; results should not be reported without substantial caveats - ☐ Push poll / Advocacy poll: Evidence of intentional bias in question design; results should not be reported as reflecting public opinion
Template 2: Survey Question Design Worksheet
Based on Chapter 7 Principles of Question Construction
Use this worksheet when designing or evaluating a survey question. Complete one worksheet per question.
Survey Topic: ___________
Target Population: ___________
Survey Mode (telephone / online / in-person): ___________
Step 1: Define the Concept You Are Measuring
What construct are you trying to measure? (Be as precise as possible)
Is this construct: - ☐ Attitudinal (opinions, evaluations, preferences) - ☐ Behavioral (past actions, reported behavior) - ☐ Demographic (factual characteristics) - ☐ Knowledge (factual recall) - ☐ Intentional (stated future behavior)
Why does this distinction matter for your question design?
Step 2: Draft Your Initial Question
Draft question wording:
Proposed response options:
-
-
-
-
- ☐ Don't know / No opinion (include? ☐ Yes ☐ No — justify your decision)
Step 3: Check for Common Design Errors
Review your draft question against each pitfall. Check if the problem applies and revise accordingly.
| Pitfall | Does it Apply? | How to Fix |
|---|---|---|
| Double-barreled question (asks about two things at once, e.g., "Do you support lower taxes and smaller government?") | ☐ Yes ☐ No | Split into two separate questions |
| Leading language (pushes respondents toward a particular answer, e.g., "Don't you agree that...") | ☐ Yes ☐ No | Rewrite using neutral phrasing |
| Loaded terms (emotionally charged words like "radical," "extremist," "failed") | ☐ Yes ☐ No | Replace with factual descriptors |
| False premise (assumes something that may not be true, e.g., "Since crime is rising, do you support...") | ☐ Yes ☐ No | Remove the factual claim or verify it |
| Acquiescence bias (question worded so "agree" / "yes" is the socially desirable answer) | ☐ Yes ☐ No | Use a forced choice or balance agree/disagree |
| Abstract framing (uses jargon respondents may not understand) | ☐ Yes ☐ No | Pilot test with lay respondents |
| Social desirability problem (respondents may be embarrassed to give their true answer) | ☐ Yes ☐ No | Consider list experiment or endorsement experiment |
| Telescoping error (time reference is vague, e.g., "recently" or "in the past") | ☐ Yes ☐ No | Specify exact time period |
| Unbalanced response options (more options on one side of neutral than the other) | ☐ Yes ☐ No | Balance the scale symmetrically |
| Missing "don't know" option (forces an opinion from those who have none) | ☐ Yes ☐ No | Add DK/NA option and decide how to handle |
| Question order effects (previous questions prime respondents or alter what this question means) | ☐ Yes ☐ No | Test different orderings; consider split sample |
| Mode incompatibility (question uses visual elements that don't work in telephone mode) | ☐ Yes ☐ No | Adapt for delivery mode |
Step 4: Revised Question
Revised question wording:
Revised response options:
Step 5: Validity and Reliability Check
Face validity: Does this question appear to measure what you intend? Get an outside opinion.
External reviewer comments: ___________
Cognitive interview plan: Will you pilot test the question using think-aloud protocols with 5–8 respondents from the target population?
☐ Yes — describe plan: _______ ☐ No — justify: _________
Split-sample test: Will you test alternative wordings in a split-sample experiment?
☐ Yes — alternative wording B: ___________ ☐ No
Step 6: Final Documentation
Final question text (verbatim, as it will appear in the instrument):
Response options (verbatim):
☐ 1: __ ☐ 2: __ ☐ 3: __ ☐ 4: __ ☐ DK/NA
Question type: ☐ Forced choice ☐ Multiple select ☐ Scale ☐ Open-ended
Interviewer instructions (if applicable): ___________
Analysis plan: ___________
Template 3: Demographic Analysis Template
Based on Chapter 13 Framework for Electorate Analysis
Use this template to conduct a systematic analysis of an electorate's demographic composition. Complete one template per geographic unit (state, district, county, etc.).
Geographic Unit Being Analyzed: ___________
Election / Office: ___________
Data Sources Used: ___________
Date of Analysis: ___________
Section A: Basic Demographics
| Demographic Dimension | % of Registered Voters | % of Likely Voters (your estimate) | % of 2020 Actual Electorate | Historical Trend (growing/stable/declining) |
|---|---|---|---|---|
| Race/Ethnicity | ||||
| White non-Hispanic | ||||
| Black non-Hispanic | ||||
| Hispanic/Latino | ||||
| Asian American/AAPI | ||||
| Other/Multiracial | ||||
| Education | ||||
| No college degree | ||||
| Some college | ||||
| 4-year degree | ||||
| Graduate degree | ||||
| Age | ||||
| 18–29 | ||||
| 30–44 | ||||
| 45–64 | ||||
| 65+ | ||||
| Gender | ||||
| Men | ||||
| Women | ||||
| Geography | ||||
| Urban | ||||
| Suburban | ||||
| Rural | ||||
| Religion | ||||
| White evangelical Protestant | ||||
| Other Protestant | ||||
| Catholic | ||||
| Jewish | ||||
| Muslim | ||||
| Unaffiliated | ||||
| Other |
Section B: Vote History Profile
| Metric | Value | Source |
|---|---|---|
| 2020 Presidential result (D vs. R margin) | ||
| 2016 Presidential result (D vs. R margin) | ||
| 2022 Midterm result (D vs. R margin, top of ticket) | ||
| Average D vs. R margin last 3 elections | ||
| Trend direction (shifting R / shifting D / stable) | ||
| Presidential year vs. midterm turnout gap | ||
| Estimated # of low-propensity registered voters | ||
| Estimated # of unregistered but eligible voters |
Section C: Partisan Composition Analysis
Party registration (if applicable in this state):
| Party | # Registered | % of Registered | Notes |
|---|---|---|---|
| Democratic | |||
| Republican | |||
| Independent/Unaffiliated | |||
| Third parties | |||
| Total registered |
Estimated partisan lean of unregistered eligible population:
Key demographic cross-tabulations to analyze further (list 3–5):
Section D: Subgroup Opportunities and Risks
Based on the demographic analysis, identify specific subgroups that represent strategic opportunities or risks.
| Subgroup | Size | Partisan Lean | Turnout Pattern | Strategic Implication |
|---|---|---|---|---|
Section E: Summary Assessment
In 2–3 sentences, describe the fundamental structure of this electorate:
Primary demographic coalition needed to win (based on this analysis):
Greatest demographic uncertainty or data gap:
Template 4: Voter Targeting Universe Worksheet
Based on Chapter 29 Targeting Logic and GOTV Strategy
Use this worksheet to define and size the voter universes for a specific campaign. Complete one worksheet per campaign and adjust as new data becomes available.
Campaign: ___________
Office / Race: ___________
Election Date: ___________
Analyst: ___________
Date: ___________
Step 1: Define the Win Number
| Metric | Value | How Calculated |
|---|---|---|
| Total registered voters in universe | ||
| Estimated total turnout (based on analogous election) | ||
| Estimated votes needed to win (50% + 1 of estimated turnout) | ||
| Current estimated vote base (strong Dem/Rep) | ||
| Gap between base and win number |
Step 2: GOTV Universe (Base Mobilization)
Definition: Voters who are already supportive of your candidate but who may not vote without contact.
| Criterion | Threshold | Rationale |
|---|---|---|
| Support score minimum | ≥ ___ / 100 | |
| Turnout score maximum | ≤ ___ / 100 | |
| Party registration (if applicable) | ||
| Additional filters (geography, age, etc.) |
GOTV Universe Size: ___
GOTV Resource Requirement: - Estimated doors/phone dials needed per conversion: ___ - Total contacts needed: ___ - Volunteer hours required: ___ - Priority subgroups within GOTV universe: ___________
Step 3: Persuasion Universe
Definition: Voters who are genuinely undecided or weakly partisan and who might be persuaded to support your candidate.
| Criterion | Threshold | Rationale |
|---|---|---|
| Support score range | ___ – ___ / 100 | |
| Turnout score minimum | ≥ ___ / 100 | |
| Party registration (if applicable) | ||
| Additional filters |
Persuasion Universe Size: ___
Persuasion Strategy: - Primary contact mode: ☐ Direct mail ☐ Digital ads ☐ Phone ☐ Door ☐ Other: ___ - Number of touches planned: ___ - Priority message themes (based on polling data): ___________
Persuasion Universe Breakdown by Subgroup:
| Subgroup | Size | Priority (1–5) | Primary Message |
|---|---|---|---|
Step 4: Fundraising Universe
Definition: Voters and supporters with the capacity and inclination to donate to the campaign.
| Criterion | Threshold | Rationale |
|---|---|---|
| Support score minimum | ≥ ___ / 100 | |
| Donor history (past campaigns) | ||
| Income/wealth proxies (if using commercial data) | ||
| Geographic accessibility |
Fundraising Universe Size: ___
Fundraising Target: $___
Average expected donation: $___
Events planned: ___________
Step 5: Opposition Research / Negative Universe
Definition: Voters supporting the opposing candidate who might be persuadable away from them under certain conditions (typically used for negative advertising targeting, not direct voter contact).
| Criterion | Threshold |
|---|---|
| Opposing support score | ≥ ___ / 100 |
| Persuadability indicators | |
| Other filters |
Negative Universe Size: ___
Note: This universe is typically targeted via broadcast or digital advertising rather than direct voter contact, as contacting a confirmed opponent can backfire.
Step 6: Universe Summary and Resource Allocation
| Universe | Size | Budget Allocation (%) | Primary Contact Mode | Deadline |
|---|---|---|---|---|
| GOTV | ||||
| Persuasion | ||||
| Fundraising | ||||
| Total | 100% |
Key Assumptions in This Targeting Plan:
Monitoring and Adjustment Plan: How will you know if targeting is working, and when will you recalibrate?
Template 5: Campaign Analytics Brief Template
Based on Chapter 28 — Presenting Findings to Campaign Leadership
The analytics brief is the primary communication tool between the analytics team and campaign leadership. It must be concise, actionable, and honest about uncertainty. Fill in all sections completely. Maximum recommended length: one page (printed).
CAMPAIGN ANALYTICS BRIEF
Campaign: __ Race: __ Date: ___
Prepared by: ___ Classification: ☐ Internal Only ☐ Can share with allies
HEADLINE FINDING (1–2 sentences — the single most important thing leadership needs to know)
CURRENT STANDING
| Metric | Our Candidate | Opponent | Trend |
|---|---|---|---|
| Head-to-head ballot test (LV) | ↑ / ↓ / → | ||
| Favorable / Unfavorable | / | / | |
| Among undecided LVs | |||
| Win probability estimate |
Data sources underlying these estimates: ___________
Confidence in these estimates: ☐ High (large recent N, consistent sources) ☐ Moderate ☐ Low (limited data)
KEY SUBGROUP FINDINGS
| Subgroup | Our Margin | Last Week | Change | Action Needed? |
|---|---|---|---|---|
| ☐ Yes ☐ No | ||||
| ☐ Yes ☐ No | ||||
| ☐ Yes ☐ No | ||||
| ☐ Yes ☐ No |
MESSAGE PERFORMANCE
| Message / Theme | Tested? | Net Effectiveness | Recommended Action |
|---|---|---|---|
| ☐ Yes ☐ No | |||
| ☐ Yes ☐ No | |||
| ☐ Yes ☐ No |
TARGETING STATUS
| Universe | Size | Contacts Made | % Complete | On Track? |
|---|---|---|---|---|
| GOTV | ☐ Yes ☐ No | |||
| Persuasion | ☐ Yes ☐ No | |||
| Fundraising | ☐ Yes ☐ No |
TOP 3 RECOMMENDED ACTIONS
- [Action]: ___________ By when: ___ Who owns it: ___
- [Action]: ___________ By when: ___ Who owns it: ___
- [Action]: ___________ By when: ___ Who owns it: ___
RISKS AND UNCERTAINTIES
| Risk | Probability | Impact | Mitigation |
|---|---|---|---|
| ☐ H/M/L | ☐ H/M/L | ||
| ☐ H/M/L | ☐ H/M/L | ||
| ☐ H/M/L | ☐ H/M/L |
NEXT ANALYTICS DELIVERABLE: _______ Due: _______
Template 6: Misinformation Tracking Template
Based on Chapter 26 and Capstone 2 — Monitoring and Responding to False Claims
Use this template to log, categorize, and track false or misleading claims circulating about your candidate, campaign, issue, or opponent. Maintaining a systematic log enables pattern analysis and rapid response.
Campaign / Organization: ___________
Tracking Period: __ to __
Primary Analyst: ___________
Claim Log
Complete one row per distinct false or misleading claim identified.
| Claim ID | Date First Observed | Claim Summary (25 words max) | Claim Type | Origin Source | Spread Platform(s) | Estimated Reach | Verified False? | Response Status | Response Date |
|---|---|---|---|---|---|---|---|---|---|
| 001 | ☐ Yes ☐ Misleading ☐ Unverified | ☐ None ☐ Drafted ☐ Deployed | |||||||
| 002 | ☐ Yes ☐ Misleading ☐ Unverified | ☐ None ☐ Drafted ☐ Deployed | |||||||
| 003 | ☐ Yes ☐ Misleading ☐ Unverified | ☐ None ☐ Drafted ☐ Deployed | |||||||
| 004 | ☐ Yes ☐ Misleading ☐ Unverified | ☐ None ☐ Drafted ☐ Deployed | |||||||
| 005 | ☐ Yes ☐ Misleading ☐ Unverified | ☐ None ☐ Drafted ☐ Deployed |
Claim Type Definitions
| Code | Type | Description |
|---|---|---|
| FAB | Fabricated | Entirely false; no factual basis |
| CTX | Out of context | True statement presented misleadingly |
| SAT | Satire misrepresented | Satirical content shared as real |
| MAI | Manipulated image/video | Authentic media altered |
| SYN | Synthetic media | AI-generated content |
| SPM | Spin/misleading framing | True facts, misleading implication |
| OPP | Opposition research misrepresented | Legitimate oppo distorted |
Claim Detail Sheet
Complete one Detail Sheet per Claim ID for claims rated high priority (reach > 10,000 OR picked up by mainstream media).
Claim ID: _ Date: Analyst: __
Full claim text (verbatim): ___________
Original source URL: ___________
Screenshot archived at: ___________
Fact-check sources: 1. _______ 2. _________
Why the claim is false or misleading (2–4 sentences):
Estimated spread: - Facebook shares/engagements: ___ - Twitter/X impressions: ___ - TikTok views: ___ - Mainstream media pickups: ☐ None ☐ Local ☐ National — outlets: ___
Target audience (who is sharing this and why):
Response decision: ☐ Ignore (low reach, responds draws attention) ☐ Rapid response ☐ Earned media strategy ☐ Platform report ☐ Legal review
Response asset created (URL or file path): ___________
Post-response tracking: Did the response reduce spread? ☐ Yes ☐ No ☐ Unable to measure
Weekly Summary Statistics
| Metric | This Week | Cumulative |
|---|---|---|
| New claims logged | ||
| Claims verified false | ||
| Claims rated misleading | ||
| Claims responded to | ||
| Highest-reach claim this week (ID + reach) | ||
| Claims from coordinated networks |
Template 7: Election Forecast Worksheet
Based on Chapters 17–21 — Constructing a Simple Electoral Forecast
This worksheet guides analysts through building a simple election forecast using fundamentals, polling, and structural adjustment. It is appropriate for U.S. House, Senate, gubernatorial, or presidential races. More complex races may require the computational methods described in Chapters 17–21.
Race: _______ Election Date: _______
Analyst: _______ Date: _______
Step 1: Establish the Structural Baseline
The structural baseline estimates vote share based on factors determined before the campaign begins.
| Structural Factor | Value | Democratic Lean (+) or Republican Lean (–) | Source |
|---|---|---|---|
| Prior election result (same race, 2 cycles ago) | |||
| Presidential partisanship of district/state (2020) | |||
| Midterm/open seat penalty (if applicable) | |||
| Presidential approval effect (if applicable) | |||
| Generic ballot (if applicable) | |||
| Structural baseline (weighted average) |
Notes on structural baseline: ___________
Step 2: Compile Available Polling
List all polls conducted in this race in the past 60 days.
| Poll # | Pollster | Date | N (LV) | D% | R% | D–R Margin | Weight (inverse of MoE²) |
|---|---|---|---|---|---|---|---|
| 1 | |||||||
| 2 | |||||||
| 3 | |||||||
| 4 | |||||||
| 5 | |||||||
| Simple polling average | |||||||
| Weighted polling average |
House effect adjustments applied (if any): ___________
Step 3: Adjust for Poll Quality and House Effects
| Pollster | Known House Effect (D+ or R+) | Adjusted Margin After Correction |
|---|---|---|
Adjusted polling average after house effect corrections: D+/R+ ___
Step 4: Combine Fundamentals and Polls
Most forecasters weight polls more heavily as Election Day approaches and fundamentals more heavily early in the cycle.
| Component | D–R Margin Estimate | Weight (must sum to 1.00) | Weighted Contribution |
|---|---|---|---|
| Structural baseline | |||
| Adjusted polling average | |||
| Combined point estimate | 1.00 |
Days until election: ___ Recommended polling weight for this stage: ___
Step 5: Estimate Uncertainty
| Source of Uncertainty | Contribution to Standard Deviation |
|---|---|
| Polling error (average state-level error from recent cycles: ~3 pts) | ± |
| Structural model error | ± |
| Correlated error across races (national environment shift) | ± |
| Total estimated standard deviation | ± |
Point estimate: D+/R+ ___ 90% confidence interval: D+/R+ ___ to D+/R+ ___ Win probability (assuming normal distribution): % D / % R
To calculate: Win probability ≈ NORM.DIST(point_estimate / std_dev, 0, 1, TRUE) for Democratic win probability if D-favored race, or appropriate tail depending on sign.
Step 6: Scenario Analysis
| Scenario | Assumption | Resulting Outcome |
|---|---|---|
| Base case | Current point estimate | |
| D favorable scenario | Polling systematically underestimates D by 2 pts | |
| R favorable scenario | Polling systematically underestimates R by 2 pts | |
| High turnout scenario | Electorate resembles high-enthusiasm election | |
| Low turnout scenario | Electorate skews older and more partisan |
Step 7: Final Forecast Statement
Write a one-paragraph forecast that includes: - Current best estimate (with confidence interval) - Win probability estimate - Key uncertainties and assumptions - What would change the forecast
Template 8: Ethics Review Checklist
Based on Chapter 38 — Ethical Evaluation of Analytics Projects
Use this checklist before launching any analytics project involving voter data, survey research, or political messaging. This checklist applies to campaigns, nonprofits, research organizations, and consulting firms.
Project Name: ___________
Project Description: ___________
Analyst/Reviewer: _______ Date: _______
Section A: Data Ethics
| # | Criterion | Status | Notes |
|---|---|---|---|
| 1 | Data sources are legal and properly licensed for this use | ☐ Met ☐ Concern ☐ N/A | |
| 2 | Voter file data is used only for permitted political purposes, not commercial resale | ☐ Met ☐ Concern ☐ N/A | |
| 3 | Personally identifiable information (PII) is protected with appropriate security measures | ☐ Met ☐ Concern ☐ N/A | |
| 4 | Data is not retained beyond its authorized use period | ☐ Met ☐ Concern ☐ N/A | |
| 5 | Third-party data vendors are vetted for ethical data practices | ☐ Met ☐ Concern ☐ N/A |
Section B: Research Ethics
| # | Criterion | Status | Notes |
|---|---|---|---|
| 6 | If human subjects research: IRB approval obtained or exemption documented | ☐ Met ☐ Concern ☐ N/A | |
| 7 | Survey respondents gave informed consent appropriate to the research context | ☐ Met ☐ Concern ☐ N/A | |
| 8 | Deceptive practices in research design are justified and IRB-approved | ☐ Met ☐ Concern ☐ N/A | |
| 9 | Respondent data is anonymized before analysis where feasible | ☐ Met ☐ Concern ☐ N/A |
Section C: Messaging and Targeting Ethics
| # | Criterion | Status | Notes |
|---|---|---|---|
| 10 | Messaging is truthful; no demonstrably false claims are being targeted to voters | ☐ Met ☐ Concern ☐ Violation | |
| 11 | Targeting does not discriminate on protected characteristics in ways that constitute voter suppression | ☐ Met ☐ Concern ☐ N/A | |
| 12 | Psychological vulnerability targeting (grief, fear, economic anxiety) uses evidence-based messages, not manipulation | ☐ Met ☐ Concern ☐ Concern |
Section D: Transparency and Accountability
| # | Criterion | Status | Notes |
|---|---|---|---|
| 13 | Sponsored content is clearly labeled with required disclosures (paid for by...) | ☐ Met ☐ Concern ☐ N/A | |
| 14 | Analytical findings are reported accurately; cherry-picking of favorable results is avoided | ☐ Met ☐ Concern ☐ Concern | |
| 15 | A designated decision-maker is accountable for the ethical compliance of this project | ☐ Met ☐ Concern ☐ No |
Section E: Ethics Summary
Number of criteria marked "Concern": _ Number marked "Violation": ___
Overall ethics assessment: - ☐ Approved: All criteria met; no concerns identified. Project may proceed. - ☐ Conditional approval: Concerns identified; proceed with listed mitigations. - ☐ Hold: Significant concerns require resolution before proceeding. See notes. - ☐ Stop: Violation identified. Project must not proceed until legal/ethics review complete.
Required mitigations before proceeding:
Escalation required: ☐ Yes (to whom: ___) ☐ No
Reviewer signature: _______ Date: _______
All templates in this appendix may be reproduced for classroom and professional use with attribution to this textbook.