Citizen segment evidence
AvailableThe clustering result identifies citizen segments and shows whether any segment has lower awareness, lower availment, lower satisfaction, or higher need for action.
Classification evidence
32 indicator modelsThe decision-tree classification uses citizen segment membership and profile variables as predictors. Most current indicator results are grouped as usable signal, which guides how strongly the result may be interpreted.
Association-rule evidence
Lift 1.04The strongest repeated service-stage pattern is: Respondents who availed the governance had a 81% likelihood of also were aware of the governance, and were satisfied with the governance (Lift: 1.04). This pattern was observed together 81.5% of the time for the eligible records.
For Governance and Response, the harmonized evidence identifies this service-stage concern: Need for Action in Traffic Management (51.5%). The recurring factor to check is Need Further Action (Governance background) appears in 19 model(s) across 4 stage(s). The repeated service-stage pattern is Awareness pattern: 81.5% confidence, lift 1.04. Together, these findings show whether the service-stage, citizen-segment, classification, and association-rule evidence point toward the same analytical interpretation.
Evidence agreement: strong consensus. The findings should be checked against local service records and field context before they are used for planning. Proposed actions, responsible offices, and monitoring indicators are presented separately in the Decision Support module.
This page harmonizes descriptive, clustering, classification, statistical, and association evidence for examination and validation. Proposed LGU actions are presented separately in the Decision Support module.
Consensus Feature Analysis
4 sources
Evidence Source Agreement
Consensus evidence checks whether different analytical outputs point toward the same interpretation. It helps avoid relying on only one model or one metric.
| Evidence Source | Main Signal | Interpretive Value | Status |
|---|---|---|---|
| Descriptive service-stage review | Need for Action in Traffic Management (51.5%). | Identifies the service-stage issue that should be checked first. | Available |
| Chi-square / statistical support | Sex shows strong relationship by Chi-square (effect 0.543, p=<0.001). | Shows which profile variable meaningfully separates citizen segments before planning targeted action. | Available |
| Decision Tree recurring variable | Need Further Action appears across 19 model(s) and 4 stage(s). | Identifies a repeated predictor that can guide validation and targeting. | Available |
| Association rule mining | Awareness pattern with 81.5% confidence and lift 1.04. | Shows which service-stage responses repeatedly appear together and should be validated. | Available |
Governance and Response has converging evidence from descriptive review, statistical support, classification, and association rules. The combined result supports a strong integrated analytical interpretation.
Recurring Predictor Evidence
15 variables
Recurring Variables Across Models
This review counts which predictors repeatedly appear with positive importance across the saved indicator-level Decision Tree models. It helps identify citizen characteristics that consistently support interpretation across service-stage outcomes.
| Recurring Variable | Evidence Group | Model Coverage | Stage Coverage | Analytical Interpretation | Evidence Relevance |
|---|---|---|---|---|---|
| Need Further Action | Governance background | 19 models Appears in 19 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | Governance and response background variables may help explain differences in public safety, disaster, and response-related outcomes. | Use this as a prompt to review response, safety, disaster, or governance-related service delivery with responsible offices. |
| MCA Dim2 | MCA profile dimension | 16 models Appears in 16 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | This is a combined profile signal from MCA. It should be read as a summary of related respondent characteristics, not as one survey question. | Review the underlying profile traits behind this MCA signal before translating it into a specific program action. |
| Satisfied/Not Satisfied | Governance background | 14 models Appears in 14 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Awareness, Availment, Satisfaction. | Governance and response background variables may help explain differences in public safety, disaster, and response-related outcomes. | Use this as a prompt to review response, safety, disaster, or governance-related service delivery with responsible offices. |
| MCA DimMagnitude | MCA profile dimension | 14 models Appears in 14 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | This is a combined profile signal from MCA. It should be read as a summary of related respondent characteristics, not as one survey question. | Review the underlying profile traits behind this MCA signal before translating it into a specific program action. |
| Source of Information | Housing and living conditions | 13 models Appears in 13 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | Household conditions or information access may be linked with how citizens know about and use LGU services. | Check whether household access conditions affect service reach, communication channels, or ability to avail services. |
| MCA Dim1 | MCA profile dimension | 12 models Appears in 12 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | This is a combined profile signal from MCA. It should be read as a summary of related respondent characteristics, not as one survey question. | Review the underlying profile traits behind this MCA signal before translating it into a specific program action. |
| Source of Drinking Water | Housing and living conditions | 9 models Appears in 9 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Awareness, Availment, Need for Action. | Household conditions or information access may be linked with how citizens know about and use LGU services. | Check whether household access conditions affect service reach, communication channels, or ability to avail services. |
| Rich or poor, citizens in our place have fair access to services from the local government. | Citizen attitude toward LGU | 8 models Appears in 8 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | Citizen attitude toward the LGU may provide governance-context evidence for public service interpretation. | Use this as governance-context evidence when interpreting service outcomes and planning citizen engagement. |
| Highest Educational Attainment | Socio-demographic profile | 8 models Appears in 8 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Awareness, Availment, Satisfaction. | This respondent profile characteristic may help explain differences in awareness, service use, satisfaction, or need for action. | Use the profile characteristic to refine target groups for information campaigns, eligibility review, or monitoring. |
| Relationship to HH Head | Socio-demographic profile | 7 models Appears in 7 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Availment, Satisfaction, Need for Action. | This respondent profile characteristic may help explain differences in awareness, service use, satisfaction, or need for action. | Use the profile characteristic to refine target groups for information campaigns, eligibility review, or monitoring. |
| Taxes and fees collected by the local government fairly reflect the quality of local programs and services it provides. | Citizen attitude toward LGU | 6 models Appears in 6 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Awareness, Availment, Satisfaction. | Citizen attitude toward the LGU may provide governance-context evidence for public service interpretation. | Use this as governance-context evidence when interpreting service outcomes and planning citizen engagement. |
| Age Group | Socio-demographic profile | 6 models Appears in 6 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | This respondent profile characteristic may help explain differences in awareness, service use, satisfaction, or need for action. | Use the profile characteristic to refine target groups for information campaigns, eligibility review, or monitoring. |
| Place of Work | Socio-demographic profile | 6 models Appears in 6 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Awareness, Satisfaction, Need for Action. | This respondent profile characteristic may help explain differences in awareness, service use, satisfaction, or need for action. | Use the profile characteristic to refine target groups for information campaigns, eligibility review, or monitoring. |
| I greatly benefit from the services provided by our local government. | Citizen attitude toward LGU | 6 models Appears in 6 indicator-level Decision Tree model(s). | 4 stages Covers 4 CSIS stage(s): Awareness, Availment, Satisfaction, Need for Action. | Citizen attitude toward the LGU may provide governance-context evidence for public service interpretation. | Use this as governance-context evidence when interpreting service outcomes and planning citizen engagement. |
| Crime committed in your municipality | Governance background | 6 models Appears in 6 indicator-level Decision Tree model(s). | 3 stages Covers 3 CSIS stage(s): Awareness, Availment, Satisfaction. | Governance and response background variables may help explain differences in public safety, disaster, and response-related outcomes. | Use this as a prompt to review response, safety, disaster, or governance-related service delivery with responsible offices. |
A recurring predictor is decision-support evidence, not proof of causation. Use it together with the indicator-level metrics, decision-tree example, clustering results, and service delivery review.
Association-Rule Evidence
8 rules
Repeated Service-Stage Patterns
Association-rule evidence shows which CSIS service-stage responses commonly appear together. Use these repeated patterns to decide which service-stage link needs validation by the LGU.
| Rule | Result Area | Repeated Pattern | Support | Confidence | Lift | Meaning | Interpretive Relevance |
|---|---|---|---|---|---|---|---|
| Rule 1 | Awareness | Citizens who availed the governance and response had a 81% likelihood of also were aware of the governance and response, and were satisfied with the governance and response (Lift: 1.04). | 52.3% seen in eligible records | 81.5% observed together | 1.04 Strong | This rule is about awareness and information reach. The linked response is observed together 81.5% of the time and appears close to the ordinary baseline rate. | Use this pattern to validate where Governance and Response information campaigns or barangay communication may need strengthening. |
| Rule 2 | Availment | Citizens who were aware of the governance and response, and were satisfied with the governance and response had a 67% likelihood of also availed the governance and response (Lift: 1.04). | 52.3% seen in eligible records | 66.6% observed together | 1.04 Strong | This rule is about movement from awareness to actual service use. The linked response is observed together 66.6% of the time and appears close to the ordinary baseline rate. | Use this pattern to check whether citizens who know about Governance and Response can actually access the service. |
| Rule 3 | Availment | Citizens who were aware of the governance and response had a 63% likelihood of also availed the governance and response, and were satisfied with the governance and response (Lift: 1.03). | 52.3% seen in eligible records | 62.9% observed together | 1.03 Strong | This rule is about movement from awareness to actual service use. The linked response is observed together 62.9% of the time and appears close to the ordinary baseline rate. | Use this pattern to check whether citizens who know about Governance and Response can actually access the service. |
| Rule 4 | Availment | Citizens who were aware of the governance and response, and felt a need for further action, and were satisfied with the governance and response had a 66% likelihood of also availed the governance and response (Lift: 1.03). | 22.0% seen in eligible records | 66.0% observed together | 1.03 Strong | This rule is about movement from awareness to actual service use. The linked response is observed together 66.0% of the time and appears close to the ordinary baseline rate. | Use this pattern to check whether citizens who know about Governance and Response can actually access the service. |
| Rule 5 | Satisfaction | Citizens who were aware of the governance and response, and availed the governance and response had a 96% likelihood of also were satisfied with the governance and response (Lift: 1.03). | 52.3% seen in eligible records | 95.9% observed together | 1.03 Strong | This rule is about citizen experience after service use. The linked response is observed together 95.9% of the time and appears close to the ordinary baseline rate. | Use this pattern to review service quality, frontline experience, and satisfaction drivers for Governance and Response. |
| Rule 6 | Availment | Citizens who were aware of the governance and response had a 66% likelihood of also availed the governance and response (Lift: 1.02). | 54.6% seen in eligible records | 65.6% observed together | 1.02 Strong | This rule is about movement from awareness to actual service use. The linked response is observed together 65.6% of the time and appears close to the ordinary baseline rate. | Use this pattern to check whether citizens who know about Governance and Response can actually access the service. |
| Rule 7 | Satisfaction | Citizens who availed the governance and response had a 95% likelihood of also were satisfied with the governance and response (Lift: 1.01). | 60.8% seen in eligible records | 94.7% observed together | 1.01 Strong | This rule is about citizen experience after service use. The linked response is observed together 94.7% of the time and appears close to the ordinary baseline rate. | Use this pattern to review service quality, frontline experience, and satisfaction drivers for Governance and Response. |
| Rule 8 | Awareness | Citizens who felt a need for further action, and availed the governance and response had a 79% likelihood of also were aware of the governance and response, and were satisfied with the governance and response (Lift: 1.00). | 22.0% seen in eligible records | 78.9% observed together | 1.00 Strong | This rule is about awareness and information reach. The linked response is observed together 78.9% of the time and appears close to the ordinary baseline rate. | Use this pattern to validate where Governance and Response information campaigns or barangay communication may need strengthening. |
Association rules show co-occurrence, not causation. A high-confidence rule should still be checked against service records, citizen feedback, and field context before implementation.
- Service-stage review: View descriptive service-stage results
- Citizen Segments: View segment profile and statistical support
- Classification: View predictor and model readiness evidence
- Association Rules: View repeated service-stage patterns
After examining and validating the harmonized evidence, continue to the Decision Support module to review planning-oriented recommendations and their traceability paths.
Open Decision Support