Transgenerational genocidal trauma of the Holodomor: Mental-health–relevant motifs in public testimonies
Bibliographic record
Abstract
The Holodomor (1932-33) persists in family narratives, household rules, and commemorations that may shape community health across generations. Using an open-source intelligence (OSINT) approach, we compiled and froze a unique-heavy corpus of public, non-academic testimonies in English and Ukrainian (N = 163) from the National Museum of the Holodomor-Genocide, the Ukrainian Canadian Research & Documentation Centre, and institutionally hosted YouTube interviews. We coded 10 motifs (presence/absence) and analysed frequencies, pairwise co-occurrences, and descriptive transmission-motif associations (Fisher’s exact/χ²). Identity and Collective Memory and Explicit Storytelling were most prevalent (n = 106 and n = 163), followed by Food-Security Behaviours (n = 75), Distrust/Institutional Mistrust (n = 64), and Scarcity Mindset/Thrift (n = 48). Food-Security Behaviours co-occurred more with Storytelling and Identity/Memory than with Ritual/Commemoration (Food × Story = 75; Food × Identity = 19; Food × Ritual = 0). Food-Security also showed a directionally positive association with Hypervigilance/Anxiety (OR = 2.05; a = 13, b = 62, c = 8, d = 80; two-sided Fisher p = .16). Associations involving Parenting/Discipline and Ritual/Commemoration were small/unstable due to very low marker-present denominators (n = 4 and n = 2). The co-occurrence hub centred on Storytelling, Identity/Memory, Food-Security, and Hypervigilance, with Distrust and Scarcity as neighbours. Public testimony, handled ethically and systematically, can serve as a pragmatic indicator system to inform trauma-aware community practice and guide mixed-methods follow-ups. Funding This study is a part of the project, The impact of the genocidal trauma of the Holodomor on the mental health of Ukrainians: From transgenerational mechanisms to community-oriented interventions, Reg. No. 0125U001724, funded by the Ministry of Education and Science of Ukraine (2024-2025). Disclosure Statement The authors reported no potential conflict of interests.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".