Sentidos de nación, reflexión pedagógica en el cambio de guion en el Museo Histórico Nacional de Chile
Bibliographic record
Abstract
This article, accompanied by the video of the temporary exhibition of the Museo Histórico Nacional de Chile, MHC (National Historical Museum of Chile), called “Sinopsis, sentidos de nación” (Synopsis, senses of the nation), reflects upon the challenges that a national history museum faces in the 21st century. This museum, created in 1911, still exhibits a story almost exclusively focused on the feat of the Nation-state and groups of power; an urban, male and military history, which ignores the historical character of minorities. Today, this historical construction results in the difficulty that national history museums, such as the Chilean one, have in transforming themselves into spaces for public dialogue about the past. The temporary exhibition of the MHN “Sinopsis, sentidos de nación”, seeks to advance towards new museological proposals that incorporate this reflection. To achieve this, it proposes a temporary journey on the different senses of belonging in the history of Chile. While the video takes us on a tour of the exhibition, this article seeks to clarify the declaration of intention of its museological and museographic approach in educational, narrative and political terms, with the aim of answering pedagogical questions about the role of a museum with a national vocation and historical dedication, as well as to incorporate minorities in an inclusive and intersectional perspective.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 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".