REVIEWER 1 - COMPREHENSIVE REVIEW
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**Review of "NUMBERSTHATSPEAK: DIGITAL WITNESSING AND MORAL TRUST IN THE WAR IN GAZA DATASET"**

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### **🔍 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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### **🔬 Step 2. Evaluation Criteria**

#### **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.

#### **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.

#### **3. Clarity & 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.

#### **4. Reproducibility & 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.

#### **5. Significance & 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.

#### **6. Ethics & 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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### **🧪 Step 3. Specific Suggestions for Improvement**

#### **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.

#### **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).

#### **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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### **📊 Step 4. Final Decision & 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.