Memorial agency, heritage dissonance, and the politics of memory in the preservation of Rio de Janeiro’s Valongo slave wharf
Bibliographic record
Abstract
Abstract The article aims to understand the tensions inherent to the commemoration of a difficult and conflicted past and the conservation of dissonant heritage. It explores the politics of memory and identity, and the power struggles that underscore the heritagisation process through a study of the transformation of Rio de Janeiro’s port in preparation to host the 2014 World Cup and 2016 Summer Olympics. The paper uses the notion of heritage dissonance to shed light upon contemporary struggles over the interpretation of the port’s contested history and explores the debates that have surrounded the 'discovery' of archeological remains, which exposed a controversial past marked by collective amnesia. The paper identifies various actions, instruments, and strategies used by various actors to either support or undermine the project, from inertia and obstructionism to memorialisation and ritual agency. The analysis of these findings reveals the transformative potential of heritage, as an instrument of empowerment in the ideological battle over collective memory, and a tool of resistance against historical denial. It discusses the way debates over heritage have stimulated public debate, inflected the official historical narrative, and allowed the legacies of slavery to infiltrate collective consciousness. The paper concludes with a discussion of how heritage dissonance can engender actions leading to conflict mediation, thereby promoting reconciliation and dialogue, and, ultimately, societal change.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.026 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".