REVIEWER 1 - COMPREHENSIVE REVIEW
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**Review of "EMPIRICAL COMMUNICATION AND TRUST CONSTRUCTION IN ACLED DATA OF THE 2023-2024 PALESTINE–ISRAEL CONFLICT"**

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### **🔍 Step 1. Summary of the Paper**

This manuscript employs a mixed-methods approach to analyze the ACLED dataset documenting the 2023–2024 Palestine–Israel conflict. The authors investigate how trust and credibility are constructed in conflict data under conditions of information asymmetry and restricted access. The study integrates quantitative analysis of 7,420 conflict events (including regional distributions, event types, and fatalities) with qualitative thematic coding of narrative fields. Key findings include: the Gaza Strip experienced 43.3% of recorded events with disproportionately high fatality rates (mean: 5.57 per event); air/artillery strikes were the deadliest event type (mean fatalities: 6.1); and qualitative analysis identified frequent references to children (28.4% of entries), hospitals (24.0%), and schools (17.8%), framing the conflict in humanitarian terms. The paper claims to contribute to understanding epistemic trust, moral witnessing, and community-based documentation as ethical infrastructure in conflict reporting.

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### **🔬 Step 2. Evaluation Criteria**

#### **1. Originality / Novelty**  
**Score: 6/10**  
The integration of quantitative ACLED data with qualitative narrative analysis in conflict zones is not entirely novel, but applying this to the 2023–2024 Palestine–Israel conflict with a focus on trust construction adds contemporary relevance. The theoretical framing around epistemic justice and moral witnessing is derived from established literature (e.g., references to oral history, decolonial theory). While the mixed-methods approach is commendable, it does not substantially advance methodological innovation. The paper’s originality lies in its empirical focus on a specific, high-profile conflict, but it falls short of introducing new theoretical or analytical frameworks.

#### **2. Scientific Rigor / Methodology**  
**Score: 5/10**  
- **Research Design:** The concurrent mixed-methods design is appropriate, but the reliance on secondary data (ACLED) without primary validation (e.g., interviews with data collectors) limits depth. The sampling strategy for qualitative analysis (systematic examination of all 7,420 entries) is thorough but may lack prioritization of high-information narratives.  
- **Flaws and Biases:** The study does not adequately address potential biases in ACLED data collection (e.g., sourcing limitations, verification challenges in conflict zones). The quantitative analysis relies heavily on descriptive statistics (frequencies, means, Pearson correlations), but inferential statistics or regression models are absent, weakening causal claims. The qualitative coding process, while detailed, lacks inter-coder reliability measures.  
- **Ethical Approval:** The use of publicly available, anonymized data is ethically sound, but the paper does not explicitly state compliance with institutional review board (IRB) standards for secondary data analysis.

#### **3. Clarity & Presentation**  
**Score: 7/10**  
The paper is generally well-structured, with clear sections and logical flow. However, the writing is occasionally dense and jargon-heavy (e.g., "epistemic resistance," "data-mediated witnessing"), which may hinder accessibility. Tables are informative but could be better integrated with the text (e.g., explaining implications of regional disparities in Table 2). The abstract and conclusions accurately reflect the findings but overstate theoretical contributions (e.g., "development of methodological approaches" is vague). Figures are absent; visualizations of temporal trends or thematic networks would enhance clarity.

#### **4. Reproducibility & Transparency**  
**Score: 4/10**  
- **Methods:** The description of quantitative and qualitative procedures is detailed but incomplete. For example, the qualitative coding framework (e.g., codebook, decision rules for thematic development) is not provided. The handling of missing data ("listwise deletion") is mentioned but not justified.  
- **Data/Code Availability:** No mention of data or code sharing. ACLED data is publicly available, but the processed dataset (e.g., merged quantitative-qualitative data) and analysis scripts are not referenced.  
- **Statistical Robustness:** Pearson correlations are reported for actor interactions, but assumptions (e.g., linearity, normality) are not checked. The civilian fatality age estimates (Table 5) are described as "estimated from reports" without methodological transparency (e.g., estimation techniques, uncertainty ranges).

#### **5. Significance & Impact**  
**Score: 7/10**  
The paper addresses an important problem: trust in conflict data amid information asymmetry and humanitarian crises. The focus on the 2023–2024 Palestine–Israel conflict ensures topical relevance, and the findings could inform humanitarian policy, data ethics, and conflict reporting. However, the impact is limited by methodological constraints (e.g., secondary data, lack of primary insights). Experts in conflict studies or humanitarian informatics may find the mixed-methods approach useful, but the paper does not offer field-changing insights.

#### **6. Ethics & Integrity**  
**Score: 8/10**  
The authors demonstrate ethical reflexivity by acknowledging power dynamics in knowledge production, secondary data limitations, and the traumatic nature of conflict documentation. No evidence of plagiarism or data manipulation. However, the paper could more explicitly discuss potential biases in ACLED data (e.g., underreporting, political influences) and the researchers’ positionality (e.g., how their perspectives shaped interpretation). Conflicts of interest are not mentioned but are unlikely given the anonymous authorship.

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### **🧪 Step 3. Specific Suggestions for Improvement**

#### **Major Flaws to Address:**  
1. **Methodological Rigor:**  
   - Incorporate inferential statistics (e.g., regression models) to test relationships between variables (e.g., event types and fatalities).  
   - Address ACLED data limitations explicitly: discuss sourcing biases, verification processes, and how missing data may affect findings.  
   - For qualitative analysis, report inter-coder reliability metrics and provide a codebook in supplementary materials.  
2. **Theoretical Contribution:**  
   - Clarify how the study advances epistemic trust or moral witnessing theory beyond applying existing frameworks.  
   - Differentiate findings from prior mixed-methods conflict studies (e.g., cite specific gaps in literature).  
3. **Reproducibility:**  
   - Share processed datasets and analysis scripts in a repository.  
   - Detail qualitative coding procedures (e.g., examples of open/axial coding, theme development).  

#### **Minor Flaws:**  
- Reduce jargon and improve readability for interdisciplinary audiences.  
- Include visualizations (e.g., time-series plots, thematic maps) to complement tables.  
- Fix formatting inconsistencies (e.g., hyphenation in the title, undefined acronyms like "ACLED" in abstract).  
- Proofread for minor typos (e.g., "constrUC - TION" in title).  

#### **Additional Experiments/Analyses:**  
- Conduct sensitivity analyses for civilian fatality estimates (e.g., bootstrap confidence intervals).  
- Compare ACLED data with other sources (e.g., UN reports, local NGOs) to triangulate findings.  
- Add a case study of specific events to illustrate qualitative themes in depth.  

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

#### **Overall Score: 6/10**  
The paper presents a timely analysis of trust in conflict data using a mixed-methods approach, with strengths in ethical reflexivity and integration of quantitative-qualitative evidence. However, methodological limitations (e.g., reliance on descriptive statistics, lack of primary data) and modest theoretical contributions reduce its rigor and impact. The study would benefit from deeper analytical methods and greater transparency.

#### **Recommendation: Borderline**  
**Justification:** While the paper addresses an important topic and employs a relevant methodological framework, it falls short of the novelty and rigor expected for a high-impact journal. The findings are descriptive rather than explanatory, and the lack of primary data or advanced statistical analysis limits its contribution. With major revisions (e.g., robust statistical testing, addressing data biases, enhancing reproducibility), the manuscript could meet publication standards. However, in its current form, it is not suitable for acceptance.