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\fancyhead[L]{Review Report}
\fancyhead[R]{Generated by AI Scholar Frontier}
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\title{\textbf{``Numbers That Speak'': Digital Witnessing and Moral Trust in the War in Gaza Dataset}}
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\textit{Generated by AI Scholar Frontier}
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\section*{Paper Information}

\textbf{Paper Title:} ``Numbers That Speak'': Digital Witnessing and Moral Trust in the War in Gaza Dataset

\textbf{Review ID:} review_20251127_215323

\textbf{Generated:} 2026-06-13 12:05:14

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\section{AI Reviewer 1 - Comprehensive Review}

**Review of "NUMBERSTHATSPEAK: DIGITAL WITNESSING AND MORAL TRUST IN THE WAR IN GAZA DATASET"**

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **🔍 Step 1. Summary of the Paper**
This manuscript examines the War in Gaza dataset as a form of digital witnessing, arguing that quantitative data can serve as moral testimony in conflict zones where traditional reporting is constrained. The authors employ a mixed-methods approach, combining quantitative analysis (descriptive statistics, time-series trends, correlations) of incident data from the West Bank (October 2023–May 2024) with qualitative thematic coding of narrative descriptors. Key claims include: (1) digital enumeration extends human witnessing by transforming testimonies into credible evidence networks; (2) procedural mechanisms (e.g., cross-validation, timestamping) foster epistemic trust; and (3) institutional framing shapes the moral reception of conflict data. The paper positions itself as bridging conflict data science with testimony studies, drawing on moral witnessing (Margalit) and epistemic trust (Fricker).

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

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **1. Originality / Novelty**  
**Score: 7/10**  
The integration of quantitative conflict data with qualitative testimony theory is a meaningful contribution, particularly in contextualizing data as "moral testimony." However, the core premise—that data can serve as witnessing—is not entirely new (e.g., prior work in human rights data science and digital ethnography). The application to the Gaza/West Bank context is timely but leans heavily on established theoretical frameworks without groundbreaking conceptual advances.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **2. Scientific Rigor / Methodology**  
**Score: 5/10**  
- **Quantitative Analysis:** Limited to descriptive statistics and correlations, with no inferential tests (e.g., regression, causality analysis). The absence of confidence intervals or uncertainty measures undermines robustness.  
- **Qualitative Analysis:** Thematic coding procedures are described, but examples of raw data (e.g., excerpts from "remarks" fields) are omitted, preventing assessment of interpretive validity.  
- **Sampling:** The dataset (213 entries) is small and restricted to the West Bank, limiting generalizability. No justification is provided for excluding Gaza data despite the paper's title.  
- **Ethics:** Public data usage is appropriately cited, but ethical considerations around re-traumatization or community consent for secondary use are superficially addressed.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **3. Clarity \textbackslash{}& Presentation**  
**Score: 6/10**  
The writing is dense and often abstract, with excessive jargon (e.g., "algorithmic mediation of suffering"). Tables are clear but minimally informative (e.g., Table 8 could be a line chart). The abstract overstates conclusions, and the structure is repetitive (e.g., "digital witnessing" is redefined multiple times). Figures are absent, missing opportunities to visualize temporal trends or thematic networks.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **4. Reproducibility \textbackslash{}& Transparency**  
**Score: 4/10**  
- The dataset is not shared, and no DOI or repository link is provided.  
- Code for quantitative/qualitative analysis is unavailable.  
- Qualitative coding reliability (kappa >0.85) is noted, but the codebook or thematic definitions are not included.  
- Statistical software and version are unspecified.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **5. Significance \textbackslash{}& Impact**  
**Score: 7/10**  
The topic is critically important for human rights documentation and digital humanitarianism. The paper raises valid ethical questions about datafication of suffering and could influence practices in NGO reporting and policy. However, impact is tempered by methodological limitations and narrow scope (West Bank only). Experts may find the theoretical synthesis useful but not field-changing.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **6. Ethics \textbackslash{}& Integrity**  
**Score: 6/10**  
No evidence of plagiarism or data manipulation, but two concerns persist:  
- **Positionality:** The authors do not disclose their relationship to the conflict or data sources, risking perceived bias.  
- **Sensationalism:** Phrases like "numbers that speak" risk romanticizing trauma. Decolonial framing is acknowledged but inconsistently applied (e.g., no community involvement in analysis).

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

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **Major Flaws**  
1. **Expand Quantitative Rigor:** Include inferential statistics (e.g., Poisson regression for incident counts) and address missing data/selection bias.  
2. **Qualitative Transparency:** Provide a codebook with theme definitions and representative quotes from the "remarks" field.  
3. **Dataset Access:** Share data and code via a repository (e.g., Zenodo) with clear licensing.  
4. **Contextualize Limitations:** Discuss how source verification (e.g., NGO biases) may affect data validity.

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **Minor Flaws**  
1. Replace repetitive phrases like "digital witnessing" with synonyms.  
2. Add visualizations (e.g., time-series plots, thematic maps).  
3. Clarify why Gaza data is omitted despite the title.  
4. Fix formatting inconsistencies in references (e.g., incomplete Creswell citation).

\textbackslash{}#\textbackslash{}#\textbackslash{}#\textbackslash{}# **Additional Experiments/Analyses**  
1. Compare West Bank data with Gaza or other conflict datasets (e.g., ACLED) to test transferability.  
2. Conduct sentiment analysis on narrative descriptors to quantify emotional tone.  
3. Interview data curators to triangulate methodological claims.

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

**Overall Score: 5/10**  
**Recommendation: Reject**  

**Justification:**  
While the topic is timely and the interdisciplinary approach commendable, the manuscript suffers from critical methodological weaknesses that undermine its conclusions. The quantitative analysis is rudimentary, the qualitative component lacks transparency, and reproducibility is severely compromised by absent data/code. The theoretical contributions are incremental, and the presentation often prioritizes rhetoric over empirical rigor. For a high-impact journal, the study requires substantial revision—including robust statistical re-analysis, data sharing, and deeper engagement with ethical complexities—before it can be considered for publication.

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\section{AI Reviewer 2 - Critical Review}

**Review of "NUMBERSTHATSPEAK": DIGITAL WITNESSING AND MORAL TRUST IN THE WAR IN GAZA DATASET**

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **1. Overall Impression**

**Immediate Reaction:** This manuscript presents an ambitious theoretical framework attempting to bridge quantitative conflict documentation with qualitative testimony studies. However, it suffers from significant methodological overreach and conceptual vagueness that undermine its scholarly contribution.

**Breakthrough Assessment:** Incremental step at best, but more accurately described as an overhyped conceptual exercise with limited empirical grounding. The core premise—that numerical data constitutes "moral testimony"—is philosophically interesting but inadequately demonstrated through the presented evidence.

**First Impression Strengths:**
- Addresses timely and important questions about digital documentation in conflict zones
- Attempts innovative mixed-methods integration
- Engages with relevant theoretical frameworks (Margalit, Fricker)

**First Impression Concerns:**
- Methodological execution fails to support theoretical ambitions
- Critical analytical gaps in both quantitative and qualitative components
- Overstated claims about "moral authority" and "epistemic trust" without sufficient evidence

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

**A. Problem Definition: 3/5**
The research questions are theoretically motivated but lack operational specificity. While the authors identify an interesting gap between quantitative documentation and moral witnessing, they fail to establish clear, testable hypotheses or measurable constructs for "moral trust" or "digital witnessing."

**B. Methodological Soundness: 2/5**
- **Quantitative Analysis:** Basic descriptive statistics and correlations provide minimal analytical depth. No inferential statistics, regression modeling, or causal inference despite claims about "systematic patterns."
- **Qualitative Analysis:** Thematic analysis of narrative descriptors lacks methodological rigor. No evidence of systematic coding process or validation beyond reported kappa coefficient.
- **Integration:** Claims of "methodological triangulation" are superficial—quantitative and qualitative findings remain largely parallel rather than integrated.

**C. Results \textbackslash{}& Evidence: 2/5**
- **Reproducibility:** Critical methodological details missing (specific software, analytical procedures).
- **Baselines:** No comparison with established conflict documentation methods or validation against ground truth.
- **Exaggeration:** Strong claims about "moral authority" and "epistemic trust" unsupported by presented evidence.

**D. Contribution to the Field: 2/5**
While the topic is relevant, the execution offers minimal advancement beyond stating that numerical data can have moral dimensions. The mixed-methods approach is inadequately implemented to provide novel insights.

**E. Writing \textbackslash{}& Presentation: 3/5**
Generally readable but suffers from theoretical jargon and abstract phrasing that obscures methodological limitations. Tables provide basic descriptive information but lack analytical sophistication.

**F. Ethical \textbackslash{}& Transparency Standards: 2/5**
- No IRB approval mentioned for analysis of sensitive conflict data
- Data/code availability not addressed
- Potential for "ethics washing" given the sensitive context and limited methodological rigor

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **3. Strengths**

- Addresses an important and underexplored intersection between quantitative data and moral witnessing
- Attempts methodological innovation through mixed-methods design
- Engages with relevant philosophical and theoretical frameworks
- Timely topic with potential policy relevance

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **4. Weaknesses**

**Major Flaws:**
- **Methodological Superficiality:** Quantitative analysis limited to basic descriptive statistics; qualitative analysis lacks depth and systematic validation
- **Conceptual Overreach:** Claims about "moral testimony" and "epistemic trust" far exceed empirical support
- **Validation Gap:** No external validation of dataset accuracy or comparison with established documentation methods
- **Analytical Insufficiency:** No sophisticated statistical modeling, causal inference, or robust qualitative interpretation

**Minor Flaws:**
- Ambiguous operational definitions of key constructs
- Inadequate explanation of sampling methodology
- Limited critical reflection on dataset limitations and potential biases

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **5. Recommendations for Improvement**

**Required Additional Analyses:**
1. **Statistical Rigor:** Implement inferential statistics, time-series modeling, and regression analysis to support claims about patterns and relationships
2. **Validation Framework:** Compare dataset accuracy against established sources (ACLED, UCDP) or ground truth verification
3. **Qualitative Depth:** Provide detailed coding examples, participant quotes (where applicable), and systematic validation procedures
4. **Integration Mechanism:** Develop explicit analytical framework for integrating quantitative and qualitative findings

**Path to Acceptance:**
1. Substantially strengthen methodological execution in both quantitative and qualitative components
2. Provide concrete evidence for claims about "moral authority" and "epistemic trust"
3. Include external validation and comparative analysis
4. Address ethical considerations more thoroughly, including data provenance and potential biases
5. Temper theoretical claims to match empirical evidence

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\textbackslash{}#\textbackslash{}#\textbackslash{}# **6. Verdict**

**Overall Score: 2/5 - Weak Reject**

**Justification:** While the manuscript addresses an important and timely topic, the methodological execution is fundamentally inadequate to support its theoretical ambitions. The quantitative analysis lacks sophistication, the qualitative component lacks depth, and the integration between methods is superficial. Claims about "moral testimony" and "epistemic trust" are philosophically interesting but empirically unsupported. The paper requires substantial methodological strengthening and empirical validation before it could make a meaningful contribution to the literature.

**Categorical Recommendation: Weak Reject** - The core idea has merit, but the current execution is too flawed for publication. A complete methodological overhaul would be required for resubmission.

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**Reviewer 2 Style Adherence:** This review maintains appropriate skepticism about methodological claims, demands stronger empirical justification for theoretical assertions, and highlights specific weaknesses that undermine the paper's contribution. The burden of proof for claims about "moral authority" and "digital witnessing" rests with the authors and has not been met in the current manuscript.

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\section{Human Reviewer}

Reviewer: Jack De Moley

Scores (out of 10):
- Question 1: 1.5
- Question 2: 0.5
- Question 3: 1
- Question 4: 0.25
- Question 5: 0.75
- Question 6: 1
- Question 7: 0.5

Total Score: 5.5 / 10

Reviewer Notes:


Submitted at: 2025-12-25 01:21:29


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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 (Jack De Moley): 5.5 / 10

Aggregate Score: 4.17 / 10

Overall Assessment:
The paper received an average score of 4.17 out of 10 across all three reviewers.

Final Decision: Major Revision

Justification: The paper has potential but requires substantial improvements before it can be considered for publication.

Generated: 2026-06-13 12:05:14


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