Research

Selective Sources, Scrutiny, and the Absence of Standards in Military Conflict Coverage

By Tatiana Glezer

Author

Tatiana Glezer

Artwork

Hili Slav

The Problem

The article addresses what the author identifies as a recurring problem in journalism studies: the lack of operational and measurable standards for core professional values such as objectivity, impartiality, and accuracy. Glezer argues that while these ideals are central to journalistic ethics, they remain vague in practice and difficult to translate into systematic indicators. As a result, the field lacks unified tools for identifying, measuring, or comparing distortions such as framing bias or selective sourcing. The author contrasts this with adjacent fields such as marketing, where computational methods (e.g., sentiment analysis) have been widely adopted.

A second, more concrete dimension of the problem concerns conflict reporting by legacy media institutions. The author argues that, absent measurable standards, authoritative outlets such as the BBC, Reuters, The Guardian, and The New York Times can shape global understanding of events in ways that go uncorrected even when reporting is later shown to have been inaccurate. The paper cites recent BBC controversies — including a fabricated Trump video and a documentary featuring the son of a Hamas leader used without disclosure — as cases where institutional response came only after external pressure. The author contends that frequent repetition of particular formulations can begin to function as a substitute for evidence.

As an illustration of the broader stakes, Glezer points to the August 2025 UN Commission of Inquiry determination that Israel is committing genocide in Gaza. The author notes that among the commission's evidentiary supports was an 83% civilian-casualty ratio drawn from a Guardian article, and argues that this figure rests on 8,900 individually named militants only, excluding those assessed to have been militants but not individually identified. The author further argues that had the IDF's last published estimate (approximately 17,000 militants, autumn 2024) been compared with the total death toll reported 11 months later, the corresponding civilian-casualty ratio would have been closer to 68%.

The author presents this case as an example of how legacy-media reporting can become part of the evidentiary basis for an international legal determination.

Approach and Findings

Glezer's study is a comparative quantitative content analysis of casualty reporting in the Gaza war across eight major English-language outlets. The research was conducted in two stages: a pilot phase (February–March 2024), analyzing an initial sample of 211 articles, followed by the main analysis. Overall, the study comprised 1,378 articles published between February and June 2024, including the pilot sample. The study employed a theory-driven multiple-case design examining eight major non-conservative media organizations. The outlets were selected based on prior research identifying them as analytically relevant to conflict reporting, their influence in the global news ecosystem, and, in the case of Reuters and AP, their role as leading international news agencies. The final sample included CNN, BBC, The New York Times, The Guardian, The Washington Post, ABC, Reuters, and The Associated Press, with per-outlet samples ranging from 111 to 245 articles. The author notes that the findings were first published in aggregated form in Andrew Fox's Henry Jackson Society report and in The Telegraph (December 2024); the DHR article presents the detailed per-outlet data for the first time.

The analytical framework acknowledges bilateral source-reliability problems. The author notes that the Gaza Ministry of Health (MoH) data is controlled by Hamas's de facto military wing, does not distinguish combatants from civilians, and is described by the UN Office for the Coordination of Humanitarian Affairs as not having undergone independent verification. The author also notes that the IDF does not publicly disclose its methodology for distinguishing combatants from civilians, that its press office is difficult to reach in practice, and that official casualty estimates are published through different government channels rather than a single source. The last official IDF estimate (17,000 militants killed) was released in autumn 2024, while a subsequent estimate of 25,000 was published by the Israeli Prime Minister on an official Government of Israel platform. The author argues that neither source provides transparent, verifiable information on civilian deaths specifically, yet only one of them is systematically cited without qualification.

Statements containing casualty-related information were manually identified and isolated for standardized comparison. The excerpts were coded using a 76-item scheme organized into three domains — casualty information, source attribution, and contextual framing. To minimize interpretive bias, the contextual framing variables were excluded from the final analysis, leaving 39 variables. Each statement was independently coded by two researchers and reviewed by a third, with reported inter-coder reliability of Krippendorff's α = 0.82. The author reports that the team consisted of unpaid international volunteers not institutionally affiliated with a single organization, and that the full dataset and coding structure are publicly available.

The study reports that Gaza MoH figures appeared in 100% of publications citing casualty data, while Israeli data appeared in approximately 3%. According to the author, no article in the sample explicitly identified civilians as a distinct category within the aggregate totals — meaning a civilian-only reading of the totals emerges by default from how figures are presented. References to Israeli estimates of Hamas combatants killed were extremely rare across all outlets, with The New York Times not citing such figures at all and The Guardian and CNN doing so in approximately 1% of articles; AP and ABC reported them in 7–8% of relevant coverage.

The study reports inconsistent transparency regarding the limitations of Gaza MoH data. According to Glezer, AP and The Washington Post clarified that MoH figures do not distinguish civilians from combatants in approximately 40–43% of relevant articles, while BBC, Reuters, CNN, and The New York Times did so far less frequently; across the dataset, the disclaimer appeared in approximately 15% of analyzed publications. Attribution practices varied as well: The Guardian most frequently presented MoH figures without explicit source attribution (approximately 43%), while the BBC did so in approximately 2% of cases. The BBC most consistently emphasized the MoH's institutional affiliation with Hamas (approximately 95% of relevant articles), while NYT, Washington Post, CNN, Reuters, and AP did so far less frequently (roughly 2–16%). The author notes that the relatively low rates for Reuters (16%) and AP (14%) are consequential, since these agencies serve as the basis for many downstream publications.

The study also reports an asymmetry in expressions of doubt across sources. According to the data, the BBC questioned Israeli statistics in 43% of relevant cases while never questioning MoH figures; The Guardian and AP showed similar asymmetric patterns. The Washington Post displayed the largest asymmetry in the data, questioning Israeli figures in 71% of cases compared with 1% for MoH figures. The author notes that the Israeli-data subsample is small (28 articles), which limits outlet-level statistical generalization, although the aggregate pattern remains. As examples of downstream effects in public discourse, the author cites a CNN host referring to "35,000 civilians dying," although the reported death toll at the time was approximately 35,000 and included militants; a CBS interview guest making the same conflation; and a UN video titled 25,000 Civilians Killed in Gaza War, published when the reported total death toll was approximately 25,000 but presenting the total as a civilian figure.

Implications

The author argues that insufficiently clear and unified standards for reporting casualty data can produce systematic asymmetries in how information is sourced, attributed, and questioned, and that these asymmetries contribute to what the paper calls an "authoritative version of reality." According to Glezer, these patterns extend beyond public discourse and can shape institutional and legal determinations — with the UN Commission of Inquiry case cited as a leading example.

The author also points to structural challenges facing legacy media institutions, including limited responsiveness to external criticism and pressure from the competitive dynamics of digital and social media environments. Glezer notes that despite the study's coverage in international outlets, the organizations examined have not significantly changed their casualty-reporting practices, which the author interprets as evidence that editorial cultures remain relatively insulated from methodological critique.

The study acknowledges several limitations: the sample excludes other prominent outlets such as CBS and Fox News; short-term casualty metrics (e.g., deaths over the last 24 hours) were not examined; the February–June 2024 time frame does not span the full conflict; the "Gaza" keyword filter may have excluded some relevant articles; and data-driven coding inevitably involves some degree of researcher interpretation, mitigated but not eliminated by double-coding and third-party review. On this basis, the author calls for stronger professional reflection within journalism regarding responsibility, transparency, and attribution standards.

More from this issue

Research

Mapping Affective Polarization in YouTube Shorts: A Data-Driven Analysis of Political Communication During the 2023–2024 Israel–Hamas War

Miehling addresses a methodological and empirical gap in the study of online political communication, particularly in the context of highly polarized conflicts such as the Israel–Hamas war. The author argues that digital communication consisting of user-generated content is often shaped by emotive cues that signal ideological alignment and provide insight into polarization and sentiment dynamics. However, much of the existing research on communication focuses on small-scale qualitative studies, which cannot capture such patterns on a large scale. A related problem is that computational methods capable of analyzing large volumes of text — including a technique called Aspect-Based Sentiment Analysis (ABSA), which assesses sentiment toward specific entities mentioned in text (e.g., "Israel," "Hamas," "Palestinians") rather than just the overall mood of a passage — have not been sufficiently adapted to politically charged domains. ABSA is widely used in commercial settings (for product reviews, for example); its application to political communication remains comparatively limited. Most existing computational studies focus on micro-blogging platforms such as Twitter/X, leaving algorithmically driven, visually oriented environments like YouTube Shorts understudied despite their growing importance. The author argues that YouTube Shorts play an increasingly important role in understanding accelerated communication domains, in which user-generated and state-funded media content shape the digital climate mediated by recommendation algorithms. Under these conditions, affective polarization — the emotional and moral alignment of users toward collective actors like Israel, Zionists, or Palestinians — becomes central to engagement. The paper argues that scalable tools for systematically mapping these evaluative patterns — in which individuals dislike and distrust those with opposing political views – remain underdeveloped in such platform-specific contexts.

Perspective

Governability-by-Design: Closing the Accountability Gap for Agentic AI in Digital Ecosystems

Digital-harm governance is entering a new phase. For the last decade, regulators, platforms, and researchers have focused on content, accounts, and recommendation systems: what is posted, who posted it, whether it violates policy, and how far it spreads. That framing still matters, but the rise of agentic AI shifts the problem toward whether partially autonomous systems can be meaningfully observed, constrained, and interrupted once deployed across digital environments. This is especially urgent where exclusion, harassment, and hate circulate across platforms. As early as mid-2024, OpenAI reported attempts by covert influence operations to use its models for multilingual content generation, persona creation, and cross-platform posting support. Meta's adversarial threat reporting tells a similar story, documenting coordinated inauthentic behavior across Facebook, Instagram, X, Telegram, YouTube, TikTok, and other services, including the use of generative AI for fake personas and synthetic media (Franklin & Torrey, 2024). Taken together, these reports show that AI-enabled coordination already complicates attribution, enforcement, and timely intervention across multiple platforms and jurisdictions. Agentic AI systems are generally understood as systems that can pursue goals through multi-step action rather than merely respond once to a prompt. In practice, this includes systems that can call tools, browse the web, manage memory, operate across applications, and adapt based on feedback. Not every AI agent is equally agentic: a narrow customer-service bot differs from a more open-ended system that can browse, message, trigger tools, and iterate toward a goal. Consequently, the governance challenge grows as autonomy and environmental access increase.

Legal

Without Anchor: Limits of Digital Harm Governance

Picture a person who wakes up to a coordinated campaign against their name. Across dozens of platforms, hundreds of accounts cite one another and adapt their language to whoever pushes back. The campaign is persistent and tailored. It is also, in the legally relevant sense, without an anchor. This is no longer just a thought experiment: an ecosystem is being built for AI agents to socialize, trade, and launch tokens autonomously. Against that backdrop, two capabilities, the autonomous swarm and mid-operation reprogramming, expose a problem that the law governing digital harm is structurally unequipped to solve. A legal anchor is a provider, operator, controller, or human decision-maker at whom obligations attach and toward whom liability can be directed. But these capabilities inflict harm without one. Can an autonomous agent that inflicts harm on a third party, with no human in the causal chain who decided to inflict it, be redressed under frameworks that were built on the assumption that someone, somewhere, made that decision?