Memorial landscapes and contestation: destabilising artefacts of stability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Landscapes of memorialisation are, simultaneously, sites of remembering and forgetting. As sites of remembering, memorial landscapes are instructive. Their artefacts of commemoration do not simply recall events and/or people, they extol specific values and lessons that members of their given society are silently urged to aspire to and emulate. However, such landscapes are strategically curated presenting a historical narrative that reflects and supports the dominant socio-political paradigm. Those voices that do not reflect this paradigm are silenced, symbolically excluded and hence forgotten. However, the processes of silencing and forgetting are never absolute. Alternative voices contest dominant memorialisation practices, jostling to be heard in wider societal discourse. The papers in this special issue reflect upon these struggles. Drawing on case studies from across the globe the authors of each paper trace the complexity of and contestation over landscapes of memorialisation. In doing so, this special issue contributes to the multidisciplinary understandings of remembering and forgetting in and through the landscape.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it