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Record W3205922937 · doi:10.3102/00346543211052333

Operationalizing Historical Consciousness: A Review and Synthesis of the Literature on Meaning Making in Historical Learning

2021· review· en· W3205922937 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueReview of Educational Research · 2021
Typereview
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsMcGill University
Fundersnot available
KeywordsOperationalizationConsciousnessMeaning (existential)Construct (python library)EpistemologyNegotiationSociologyDisciplineSet (abstract data type)Field (mathematics)PsychologySocial scienceComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

In response to the growing need for more relevant school history, the notion of historical consciousness has come to represent a way to help students understand the links between past, present, and future. However, translating the construct into practice in an ongoing puzzle in the field. Recently, efforts have been made to operationalize historical consciousness via a competency-based approach, but this is arguably problematic, because its proponents view historical consciousness as a hermeneutic quest for meaning yet operationalize it as a set path of mental processing. This article explores a different approach based on meaning-making practice. It does so through an extensive review and synthesis of the relevant literature, and based on the results, it suggests operationalizing historical consciousness through negotiating the presence of the past, inquiring about the past with the help of disciplinary and everyday habits of mind, and building a sense of historical being.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.059
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.549
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.059
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.341
GPT teacher head0.542
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it