Forms of Historical Oblivion and Figures of Silence in Commemorative Practices of the Black Lives Matter Movement: A Comparative Analysis of Media Discourses in English-Speaking Countries
Bibliographic record
Abstract
The Black Lives Matter (BLM) social movement has emerged as a prominent challenge to the principles and values of contemporary societies. Concurrently, the practices of cancel culture extend to the historical past as well. The primary objective of this article is to conduct a comparative analysis of forms of historical forgetting and figures of silence within the commemorative practices of BLM, as depicted in media discourses across the English-speaking countries. Making use of the critical discourse analysis methodology of N. Fairclough and S. Jäger, this study analyzes the discursive aspects of monument cancellations and key figures of silence in the media portrayal of BLM commemorative practices in the USA, Canada, the UK, and Australia. The research reveals that, despite the unique characteristics of media discourses in Australia and Canada, particularly concerning the memory of indigenous peoples, the canceling practices in the countries examined exhibit similar features. These include general forms of oblivion associated with the formation of a new identity, as outlined by P. Connerton, and the use of forgetting as a weapon, as described by A. Assmann, in the quest for symbolic capital. This study identifies and examines key figures of silence within BLM as a community of memory, including a-historical perspective of colonial era events, disproportionate focus on selected cancellation facts, invocation of collective guilt, silence over morally questionable traits of the oppressed, absence of a constructive program linking past and future, and unchecked emotional expression regarding the past.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.011 | 0.022 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".