Diasporic Spidering, Counter-Archiving, and Collective Memory
Bibliographic record
Abstract
Diasporic Spidering, Counter-Archiving, and Collective Memory is an experimental exhibition that aims to foster community through interdisciplinary and intercultural collaboration and uncover a process of critical curatorial practice. This exhibition displays select videos from Rhodnie Désir’s BOW’T TRAIL and features a commissioned sculptural installation by Alberto Castillo titled Silk Strands, Silk Traces. Travelling across the Americas to experience the ports and portals of ancestral memory that exist within the aftermath of Transatlantic Slave Trade, Désir’s BOW’T TRAIL offers a poignant yet poetic entry into the histories of migrants who left voluntarily and involuntarily. Considering the global map as a web further situates Désir’s choreographic methodology as a ‘diasporic spidering,’ itself. Nadine George-Graves explains that “Diasporic heritage survives despite the odds, and Anansi’s processes of journeying, gathering (wisdom and memory), gaining insight, sharing, and connecting are diasporic spiderings.” Experimental in nature, Diasporic Spidering, Counter-Archiving, and Collective Memory explores my emergent curatorial practice as a ‘diasporic spidering,’ utilizing Desir's choreo-documentary methodology and the creation process of Silk Strands, Silk Traces as research materials. This exhibition uses the gallery space as a site for valuing choreographic methodology as an artistic product as a way of celebrating the multiplicity of Black thought, history, and communities, now.
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.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".