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Record W2953049113

Using Archives in Undergraduate Courses in the Humanities and Social Sciences

2017· article· en· W2953049113 on OpenAlexaff
Jane Arnold, Andy Parnaby, Heather Sparling

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicDigital and Traditional Archives Management
Canadian institutionsCape Breton University
Fundersnot available
KeywordsInternshipCapstoneSession (web analytics)Section (typography)Information literacyLibrary scienceLiteracyPedagogySociologyMedical educationMathematics educationPsychologyComputer scienceWorld Wide WebMedicine
DOInot available

Abstract

fetched live from OpenAlex

As part of our workshop session, we shared experiences with conference participants related to using archives as a means of enhancing student experience and learning outcomes within undergraduate courses. This report begins with a brief background explaining the history of incorporating primary source materials in humanities and social science courses at Cape Breton University (CBU), and follows with a summary of the session divided into four sections. The first section defines the concept of Primary Source Literacy, and how faculty and archivists/librarians work together to assist students develop these competencies. The second section focuses on model assignments provided by two faculty co-presenters along with an assignment development framework. The third section reflects on the Beaton Institute Internship Program, a capstone course held and supervised in the archives. The final section summarizes our discussion with participants who shared their experiences with primary source literacy instruction and questions around integrating archive-based assignments into future courses.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0090.006
Open science0.0030.013
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0100.002

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 head0.210
GPT teacher head0.299
Teacher spread0.089 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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