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Record W2299715359 · doi:10.4018/ijopcd.2016040105

The Interpretive Imagination Forum

2016· article· en· W2299715359 on OpenAlexaffabout
Karyn Cooper, Naomi Rebecca Hughes, Aliyah Shamji

Bibliographic record

VenueInternational Journal of Online Pedagogy and Course Design · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCurriculumSociologyScholarshipCurriculum studiesNormativePedagogyQualitative researchMathematics educationEpistemologyPsychologySocial science

Abstract

fetched live from OpenAlex

This article reports on a study that engaged graduate students from one Canadian university in a knowledge creation project, which produced new evidence and insights regarding pressing socio-political issues of our time. This study resulted in the creation of an instructional application known as the IIF (the Interpretive Imagination Forum), a collaborative video research application for use in higher education courses across the disciplines (e.g., anthropology, history, media studies, philosophy, queer studies, sociology, women's studies). Further, this study resulted in the development of a technology-mediated, hermeneutic tagging technique. IIF was developed as an open-source platform for conducting video research. In keeping with open-source curriculum objectives (OSC), a curriculum framework was developed, which can be used in graduate-level courses (e.g., curriculum foundations, qualitative methodology, critical inquiry). Student participants were invited to add, delete, and modify text annotations or tags, which not only resulted in broader understandings of the themes, theories, and concepts that existed within the videotaped content, but also resulted in the development of a creative and innovative instructional and learning tool. The overarching objective of this study was to circumvent linear or normative qualitative analysis and instead facilitate non-linear, creative, and organic approaches to understanding, analyzing, representing, and disseminating theories and concepts derived from video scholarship.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.047
GPT teacher head0.464
Teacher spread0.417 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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
Published2016
Admission routes2
Has abstractyes

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