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\fancyhead[L]{Review Report}
\fancyhead[R]{Generated by AI Scholar Frontier}
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\title{\textbf{``Numbers Don't Speak, People Do'': Trustworthiness in Humanitarian Casualty Reporting during the Gaza War (2024--2025)}}
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\textit{Generated by AI Scholar Frontier}
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\section*{Paper Information}

\textbf{Paper Title:} ``Numbers Don't Speak, People Do'': Trustworthiness in Humanitarian Casualty Reporting during the Gaza War (2024--2025)

\textbf{Review ID:} review_20251127_220207

\textbf{Generated:} 2026-07-17 15:59:52

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\section{AI Reviewer 1 - Comprehensive Review}

**Review of "NUMBERS DON'T SPEAK, PEOPLE DO": TRUSTWORTHINESS IN HUMANITARIAN CASUALTY REPORTING DURING THE GAZA WAR (2024–2025)**

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **🔍 Step 1. Summary of the Paper**

This mixed-methods study examines how trustworthiness is established in humanitarian casualty reporting during the 2024–2025 Gaza conflict. The paper integrates quantitative analysis of a publicly available dataset (N=20,390 records) with qualitative insights from 22 field interviews. Key findings indicate that 32.8\textbackslash{}% of documented victims were children under 18, with a modal age group of 19–30 and a consistent male majority (60\textbackslash{}%). Qualitatively, credibility is shown to emerge from procedural visibility, independent corroboration, and narrative integration rather than institutional authority. The paper claims to contribute a "two-path triangulation model" for data credibility, "range-plus-change-log" publication standards, and methodological frameworks for integrating micro-narratives with aggregate data.

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **🔬 Step 2. Evaluation Criteria**

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **1. Originality / Novelty**  
**Score: 7/10**  
The paper applies established mixed-methods approaches to a timely, high-stakes context but does not introduce fundamentally new methodologies. The "two-path triangulation" model and "range-plus-change-log" standards are pragmatic adaptations of existing verification principles rather than theoretical breakthroughs. However, the focus on distributed verification under infrastructure collapse offers a fresh perspective on credibility construction in conflict zones.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **2. Scientific Rigor / Methodology**  
**Score: 5/10**  
- **Quantitative Component:** The dataset lacks event dates, preventing temporal analysis—a critical limitation for conflict casualty research. Age/sex distributions are clearly presented, but the absence of cause-of-death or geographic data limits contextual interpretation.  
- **Qualitative Component:** Purposive sampling of 22 participants is reasonable, but remote data collection may compromise depth. Thematic analysis procedures are adequately described, though reflexivity practices could be more detailed.  
- **Integration:** Concurrent triangulation is appropriately applied, but the paper does not sufficiently address tensions between quantitative and qualitative findings.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **3. Clarity \textbackslash{}& Presentation**  
**Score: 6/10**  
The paper is generally well-structured but suffers from repetitive phrasing (e.g., "procedural visibility" appears excessively). Tables are clear but could better highlight key insights (e.g., visualizing age-sex distributions). The abstract accurately represents the study, though the title's stylized formatting ("DON'TSPEAK") is unprofessional.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **4. Reproducibility \textbackslash{}& Transparency**  
**Score: 8/10**  
Methods are described in sufficient detail, and the dataset is publicly accessible. Ethical protocols and data cleaning procedures (e.g., outlier removal) are clearly documented. However, interview guides and coding frameworks are not provided, limiting qualitative reproducibility.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **5. Significance \textbackslash{}& Impact**  
**Score: 9/10**  
The topic is critically important for humanitarian practice and policy. The paper addresses core challenges in conflict documentation and offers practical recommendations for balancing accuracy with human dignity. Findings could influence reporting standards in future crises.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **6. Ethics \textbackslash{}& Integrity**  
**Score: 8/10**  
Ethical approvals and data security measures are clearly stated. The use of a publicly sourced dataset labeled "Genocide of the Palestinian People" introduces potential bias, though the authors handle the data objectively. Conflicts of interest are appropriately disclosed.

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **🧪 Step 3. Specific Suggestions for Improvement**

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **Major Flaws**  
1. **Temporal Analysis Gap:** The absence of event dates in the dataset fundamentally limits analysis of reporting dynamics over time. The authors should either obtain dated records or explicitly justify this limitation's impact on conclusions.  
2. **Conceptual Overlap:** Key terms (e.g., "procedural visibility," "two-path corroboration") are redundantly defined and applied. Streamline and operationalize these constructs.  
3. **Sampling Justification:** Provide stronger rationale for the participant distribution (6 verification leads, 5 clinicians, etc.) and address potential selection bias from "established humanitarian networks."

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **Minor Flaws**  
1. **Title Formatting:** Correct the title's spacing and punctuation.  
2. **Repetitive Phrasing:** Reduce redundant descriptions of findings (e.g., "credibility emerges from procedural visibility" appears 10+ times).  
3. **Table Optimization:** Consolidate Tables 1–5 into a single demographic overview with highlighted trends.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **Additional Analyses**  
1. Conduct sensitivity analyses to assess the impact of outlier removal on demographic patterns.  
2. Explore statistical tests (e.g., chi-square) to validate claimed consistencies in sex distributions across age groups.  
3. Triangulate findings with external datasets (e.g., UN reports) to assess generalizability.

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **📊 Step 4. Final Decision \textbackslash{}& Justification**

**Overall Score: 7/10**  
**Recommendation: Weak Accept**  

**Justification:**  
This paper addresses a socially and academically significant topic with methodological competence and ethical sensitivity. The mixed-methods approach is appropriate, and the integration of quantitative patterns with qualitative insights strengthens the analysis. However, major limitations—particularly the lack of temporal data and conceptual redundancy—prevent a stronger endorsement. The recommended revisions are substantial but achievable within a revision cycle. If the authors address these issues, the paper could make a valuable contribution to humanitarian research and practice.

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**Confidential Comments to Editor:**  
While the paper's political context may attract scrutiny, the authors maintain a professional, evidence-based tone. I recommend ensuring that revisions do not compromise this balance. The dataset's provenance ("Genocide of the Palestinian People") warrants careful consideration, though the authors use it appropriately for demographic analysis.

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\section{AI Reviewer 2 - Critical Review}

**Review of "NUMBERS DON'T SPEAK, PEOPLE DO": TRUSTWORTHINESS IN HUMANITARIAN CASUALTY REPORTING DURING THE GAZA WAR (2024–2025)**

**1. Overall Impression**
My immediate reaction is one of methodological skepticism and substantive concern. While the topic is critically important, the execution raises fundamental questions about research rigor and objectivity. The paper presents as a mixed-methods study but demonstrates significant weaknesses in both quantitative and qualitative components. The framing appears politically charged rather than scientifically neutral, with the dataset title "Genocide of the Palestinian People" suggesting predetermined conclusions rather than open inquiry. The abstract's claim of "analytic rigor" is not fully substantiated by the methodological description.

*First impression strengths:* Addresses timely humanitarian issue, attempts methodological triangulation, acknowledges limitations.
*First impression concerns:* Questionable objectivity, dataset limitations, potential confirmation bias, overclaims about contributions.

**2. Technical \textbackslash{}& Scientific Assessment**

**A. Problem Definition: 2/5**
- Research questions are clearly stated but framed within a predetermined political narrative
- Motivation relies heavily on the assumption that "genocide" is occurring rather than treating this as an empirical question
- Insufficient critical engagement with potential biases in data collection and reporting

**B. Methodological Soundness: 2/5**
- Quantitative analysis is purely descriptive despite claims of rigor
- Dataset lacks temporal data (dates), severely limiting analytical value
- Qualitative sampling (N=22) is small and potentially unrepresentative
- No discussion of potential selection bias in dataset compilation
- Missing essential methodological details about data collection protocols

**C. Results \textbackslash{}& Evidence: 1/5**
- Quantitative findings (32.8\textbackslash{}% children, 60\textbackslash{}% male) are presented without proper context or comparison to population demographics
- No statistical testing or confidence intervals despite claims of "range-plus-change-log" standards
- Qualitative themes appear predetermined rather than emergent from data
- No evidence of hypothesis testing or falsification attempts

**D. Contribution to the Field: 2/5**
- Proposed "two-path triangulation model" lacks novelty and operational detail
- "Range-plus-change-log" concept is underdeveloped and untested
- Integration of narratives with statistics is already established in humanitarian research

**E. Writing \textbackslash{}& Presentation: 3/5**
- Generally well-structured but repetitive in findings presentation
- Tables are clear but lack sophistication
- Excessive self-citation and methodological justification

**F. Ethical \textbackslash{}& Transparency Standards: 2/5**
- IRB approval mentioned but details lacking
- Dataset availability is positive but source credibility questionable
- Political framing raises concerns about research neutrality
- No discussion of researcher positionality biases

**3. Strengths**
- Addresses important humanitarian documentation challenge
- Attempts methodological innovation through mixed methods
- Acknowledges study limitations
- Clear presentation of basic demographic patterns

**4. Weaknesses**

**Major Flaws:**
- Dataset lacks essential temporal dimension, severely limiting analytical utility
- Political framing compromises scientific objectivity from outset
- Qualitative sample size and representativeness inadequate for claims made
- No comparison to population demographics or conflict epidemiology literature
- Overstated claims of methodological innovation
- Insufficient critical examination of data source reliability

**Minor Flaws:**
- Repetitive presentation of findings
- Inconsistent citation format
- Vague descriptions of "distributed verification networks"
- Underdeveloped theoretical framework application

**5. Recommendations for Improvement**

**Required for Resubmission:**
1. Replace politically charged dataset with neutral sources or provide rigorous validation of current dataset
2. Conduct proper epidemiological analysis comparing casualty demographics to population structure
3. Substantially expand qualitative component with larger, more representative sample
4. Remove predetermined political framing and adopt neutral scientific stance
5. Include temporal analysis through alternative data sources
6. Provide detailed methodological protocols for data collection and verification

**Would Strengthen Paper:**
- Comparative analysis with other conflict casualty reporting systems
- Statistical modeling to account for potential biases
- Detailed case studies of verification processes
- Audience reception studies to test credibility claims

**6. Verdict**

**Overall Score: 1/5 - Strong Reject**

**Justification:** This paper suffers from fundamental flaws that cannot be addressed through minor revisions. The combination of politically predetermined framing, severe dataset limitations, inadequate qualitative sampling, and overstated contributions renders the research unsuited for publication in its current form. The methodological weaknesses are particularly concerning given the sensitive nature of the topic and the potential for misuse of findings. While the subject matter is important, the execution lacks the scientific rigor and objectivity required for Tier-1 publication. The authors would need to completely reconceptualize the study design, secure more robust data sources, and adopt a genuinely neutral scientific stance to produce publishable research on this topic.

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**Reviewer 2 Style Enforcement:**
- Skeptical stance maintained throughout
- Burden of proof placed squarely on authors
- Methodological weaknesses highlighted without apology
- Political framing challenged as incompatible with scientific standards
- Claims of innovation subjected to rigorous scrutiny
- Ethical concerns about neutrality and objectivity raised explicitly

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\section{Human Reviewer}

Reviewer: Prof. Rand Kate

Scores (out of 10):
- Question 1: 2
- Question 2: 1.5
- Question 3: 1.5
- Question 4: 1
- Question 5: 1
- Question 6: 1.5
- Question 7: 1.5

Total Score: 10 / 10

Reviewer Notes:


Submitted at: 2025-12-25 01:28:05


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\section{Aggregate Report}

Aggregate Review Report

This report combines the assessments from all three reviewers:

Individual Scores:
- AI Reviewer 1 (Comprehensive): 7.0 / 10
- AI Reviewer 2 (Critical): 0.0 / 10
- Human Reviewer (Prof. Rand Kate): 10 / 10

Aggregate Score: 5.67 / 10

Overall Assessment:
The paper received an average score of 5.67 out of 10 across all three reviewers.

Final Decision: Minor Revision

Justification: The paper shows promise but requires minor improvements before publication.

Generated: 2026-07-17 15:59:52


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