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Record W4407265209 · doi:10.14324/herj.22.1.03

The rise and fall of Jackdaws: lessons for designing source collections to teach history

2025· article· en· W4407265209 on OpenAlexaff
Lindsay Gibson

Bibliographic record

VenueHistory Education Research Journal · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHistoryOpen sourceComputer scienceGeographyProgramming language

Abstract

fetched live from OpenAlex

For more than a century, educators and historians have advocated for the importance of using primary sources for teaching history. One of the most innovative and popular collections of sources in the past 60 years were Jackdaws: Collections of Contemporary Documents, which were published by Jonathan Cape between 1963 and 1977. Jackdaws are folders that contain reproductions of primary and secondary sources focused on significant historical events, people, developments, themes and topics in history. In this article, I provide a brief history of Jackdaws, and explain why they were initially popular as a learning resource for teaching history, and why their popularity waned in the mid-to-late 1970s. I conclude by highlighting several lessons that can be learned from the rise and fall of Jackdaws that might help history teachers and educators design collections of primary and secondary sources for teaching history. The three reasons that best explain why Jackdaws became popular learning resources in school history classrooms between 1963 and 1977 are that they were aligned with innovative educational theories at the time, they were flexible and adaptable to diverse contexts, and they were interesting and exciting for students. Despite being heralded as a groundbreaking and revolutionary resource for teaching history, Jackdaws failed to transform history teaching and learning for four main reasons: they were too difficult for some students; they were an awkward fit for some school history curricula; they were expensive and difficult to manage; and there was a lack of pedagogical supports to help teachers use them effectively.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.358
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.114
GPT teacher head0.333
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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