Ignorance is Bliss: Memorialising Indigenous History in the United Kingdom
Bibliographic record
Abstract
As Britain strives to take more pride in its history and promote ‘British’ values in its schools, its role in North American Indigenous history has been left off the curriculum, resulting in an education that lacks any awareness of the societies whose land it colonised. After four months of studying Indigenous history and culture for the first time, this final project sought to find a way to memorialise Indigenous people and their culture in one of the countries that was most responsible for their suffering – a country that is now so able to turn a blind eye to events that didn’t occur within its shores. In doing this, this project considered the implications of memorialising events that occurred an ocean away, and the wilful or naïve ignorance of the British public. After considering various forms of memorials, this project focused on designing a memorial garden, serving partly to increase the visibility of Indigenous people to British citizens, and partly to begin educating on aspects of their culture. This resulted in research on plants, wildlife, and symbols important to Indigenous societies, and careful consideration of all features of the garden, proposing a way for Indigenous stories to be told. The final design emphasises the importance of water, nature, and community, and is proposed as a way to begin eroding the ignorance of the British public to events that should be considered part of their history, and the cultures they affected through them.
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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 | 0.017 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".