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Record W2915296637

History 650 Syllabus Spring 2007

2007· article· en· W2915296637 on OpenAlexfundno aff

Bibliographic record

VenueLa Salle University Digital Commons (La Salle University) · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicOral History, Memory, Narrative Analysis
Canadian institutionsnot available
FundersConcordia University
KeywordsSpring (device)SyllabusMathematics educationMathematicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

This seminar will provide students with the foundations for designing and executing oral history research projects.Students will read and discuss literature about oral history theory and methods and will examine how historians use oral history interviews to construct historical narratives.In addition, students will undertake fieldwork that will allow them to apply the methods and approaches studied in class.The goal of fieldwork will be to produce a collection of interviews of La Salle faculty, staff, and alumni that will contribute significantly to preserving the history of La Salle University.Most oral history projects are organized around a common theme; organizing the class project in such a way will enhance students' understanding of oral history theory and methods, facilitate problem-solving related to methodology, and give students a better appreciation for the history and mission of La Salle University.The study of oral history is a collaborative effort that challenges traditional hierarchies.Therefore, the instructor encourages a collegial approach to discussing readings and methods.Nevertheless, she assumes sole responsibility for evaluating the quality and professionalism of students' work.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.634
Threshold uncertainty score0.523

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.000
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6340.323

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 head0.019
GPT teacher head0.172
Teacher spread0.153 · 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 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

Citations0
Published2007
Admission routes1
Has abstractyes

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