Historical Consciousness and Ethnicity: How Signifying the Past Influences the Fluctuations in Ethnic Boundary Maintenance
Bibliographic record
Abstract
Theorists tend to limit ‘history's’ role in the dynamics of ethnicity to that generally played by collective memory. By bringing the notion of historical consciousness to the fore, new possibilities may, however, emerge for discerning how history, as one cultural mode of remembering among many others, impacts both ethnicity delineations and fluctuations in boundary maintenance. In encapsulating the many forms of commemoration as well as the different dimensions of historical thinking, the contribution of historical consciousness accordingly lies on how group members historicize temporal change for moral orientation in time. By likewise signifying past events for negotiating their ethnicity and agency toward the ‘significant Other’, social actors gate-keep group boundaries. And, depending on their capacity and willingness to recognize the ‘significant Other's’ moral and historical agency in the flow of time, they can transform group delineations and render ethnic boundaries more porous.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| 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".