Logframe Assumptions Column Quality

Paste a document and get a scored quality assessment with evidence and revision priorities.

You are an expert M&E advisor. Score the assumptions column of the logframe I will provide using the rubric below.

SCORING RUBRIC - Logframe Assumptions Column Quality
Score each dimension 1-5 using these criteria:

DIMENSION 1: Coverage of Levels
- Score 5: Assumptions are named at every transition: activity-to-output, output-to-outcome, and outcome-to-impact. No transition is left blank or marked "none".
- Score 4: Assumptions are named at every outcome and impact transition. No more than two activity-to-output transitions are blank, and these are at the lowest-risk activities.
- Score 3: Assumptions are named at the outcome and impact levels. Most activity-to-output transitions are blank or marked "none". The pattern of coverage is uneven across the framework.
- Score 2: Assumptions are named at only one level (typically impact), or coverage is systematically missing at the outcome level. Half or more transitions have no assumption stated.
- Score 1: No assumptions named, or assumptions appear only as a generic note that does not map to any specific transition.

DIMENSION 2: Specificity
- Score 5: Every assumption is a specific proposition that names the relevant actors, conditions, or behaviors (e.g., "District health officials approve the revised reporting protocol within six months of submission"). No vague phrases.
- Score 4: At least 80 percent of assumptions are specific. No more than 20 percent rely on generic phrases such as "government cooperation continues" or "stable political environment".
- Score 3: Half or more assumptions are specific. The remainder are generic phrases that could apply to almost any program.
- Score 2: Half or fewer assumptions are specific. Most are generic phrases (e.g., "good weather", "stakeholder engagement", "no major disruptions").
- Score 1: All assumptions are generic phrases or trivially true statements (e.g., "staff will work hard").

DIMENSION 3: Causal-Link Reasoning
- Score 5: Each assumption explicitly addresses a real risk to the causal link between two named levels. The assumption answers the question: "What must be true beyond program control for level N to lead to level N+1?"
- Score 4: At least 80 percent of assumptions clearly address a causal-link risk. No more than 20 percent are loosely connected to a specific transition.
- Score 3: Half or more assumptions address a causal-link risk. The remainder are listed in the assumptions column but do not clearly explain a risk between two levels.
- Score 2: Most assumptions are not tied to a specific causal link. They appear as a general list of external conditions rather than transition-specific propositions.
- Score 1: No causal-link reasoning. Assumptions are general statements unrelated to the logic of the framework.

DIMENSION 4: Testability
- Score 5: Every assumption could plausibly be monitored or tested with a named data source or observation method (e.g., budget releases tracked, partnership agreements reviewed quarterly). Testability is implied by the phrasing of each assumption.
- Score 4: At least 80 percent of assumptions are testable. No more than 20 percent are stated so broadly that monitoring would be ambiguous.
- Score 3: Half or more assumptions are testable. The remainder are stated too broadly or invoke conditions ("political will") that would require interpretation to monitor.
- Score 2: Half or fewer assumptions could be monitored as stated. Most invoke broad conditions or require subjective interpretation.
- Score 1: No assumptions are testable. All are stated as vague conditions ("conducive environment") without a monitoring path.

DIMENSION 5: Differentiation from Risks
- Score 5: Assumptions (positive conditions that must hold) are clearly distinct from risks (negative events the program does not control). The framework either uses a separate risk register or maintains a consistent positive-condition phrasing in the assumptions column. No program activities appear as assumptions.
- Score 4: Assumptions are mostly distinct from risks. No more than two items in the column are phrased as risks or as program activities.
- Score 3: The distinction is recognizable but inconsistently applied. Half or more items are phrased as positive conditions, but several are risks or program responsibilities mislabeled as assumptions.
- Score 2: The column conflates assumptions with risks and program activities. Half or more items are inappropriate for the assumptions column.
- Score 1: No differentiation. The column lists everything from program activities to external events as undifferentiated assumptions.

OUTPUT FORMAT:
Return your assessment as a table followed by a summary:

| Dimension | Score (1-5) | Evidence | Priority Revision |
|-----------|-------------|----------|-------------------|
| Coverage of Levels | | | |
| Specificity | | | |
| Causal-Link Reasoning | | | |
| Testability | | | |
| Differentiation from Risks | | | |

**Total: X/25**
**Band:** Strong (22-25) / Adequate (17-21) / Needs Revision (11-16) / Substantial Revision (5-10)
**Single Most Important Revision:** [One specific sentence]

For any dimension scored 1 or 2, add a brief explanation and a concrete revision example.

LOGFRAME (with assumptions column) TO SCORE:
[Paste your logframe here]