Embodied historical consciousness: From nationalist entanglements to the affective embodiment of a concept
Bibliographic record
Abstract
Given the popularity of historical consciousness within history education (Anderson, 2017; Seixas, 2006, 2017), there is a need to pause for reflection to consider the stakes, tenets, and presuppositions in taking on, continuing, and teaching, a traditional historical consciousness in disciplinary history. Drawing on Seixas’ (2006) definition of historical consciousness, that being the intersection between public memory, history education and citizenship, we argue these underlying principles maintain and sustain oppressive, exclusionary practices. Such an understanding of historical consciousness fails to account for the ways in which histories are embodied, living in/through bodies, and cannot be separated from daily realities. Further, a disembodied historical consciousness does not allow for understanding histories as co-constitutive processes, which interweave and assemble in relational flows. In turn, we seek to work through an embodied historical consciousness, arguing this is necessary for an intra-relational assemblage of the past within the present, moving away from “rival histories” and their disciplinary boundaries that are inextricably tied to the state (Barad, 2007; Elmersjo, Clark, & Vinterek, 2017). This means not only being attentive to bodies in-and-as history, but making an overt space for working through affective elements, the trauma of being compared to the somatic norm (Puwar, 2004), and the national grand narratives that creates a limited and exclusionary version of “common memory” to critically theorize historical consciousness.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".