Search for Ancestral Roots in Morgan Jerkins’s Wandering in Strange Lands
Bibliographic record
Abstract
Many African Americans seek to unravel their history and ancestral roots, much of which was lost during the Great Migration that took place between 1916 and 1970. Morgan Jerkins’s Wandering in Strange Lands (2020) explores the history and the ancestral roots of the Jerkins family, along both the paternal and maternal lineages. Written as a memoir, rather than a historical or genealogical report, the narrative is supported by documents, records, transcripts, photos and interviews conducted by Jerkins herself. Her research uncovers the stories of other African-Americans and their native identity that sheds more light on Jerkins’s own roots, as well as the traditions of Blacks in general. Using a postcolonial lens, themes of migration, dislocation, ethnicity, marginality, Creole identity and diaspora are examined not only from the historical and genealogical viewpoint of the Jerkins family, but also from the perspective of the major groups of the Great Migration, who left the American South for other cities. Eventually, Jerkins’s arduous journey uncovers her family’s hidden past, a heritage that has been influenced by the Great Migration and the displacement of African-Americans leaving hard life conditions in search of better job opportunities in the Northeast, the Midwest, and the West Coast, in particular. The Great Migration was an attempt by Blacks to release themselves from the shackles of the oppression of White supremacy. Jerkins manages to find her heritage—language, rituals, beliefs, symbols and traditions intertwined with superstitions—and she is able to connect with her tribal roots and legacy.
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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 | 0.001 | 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 | 0.020 | 0.014 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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".