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Record W2186935327

Aesthetic Representations of Community

2008· article· en· W2186935327 on OpenAlexaboutno aff
Joi Freed-Garrod, D’Arcy Martin, Jennifer Denton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsConversationNarrativeSoundscapePedagogyInterpretation (philosophy)Class (philosophy)Social constructivismEthnographyRepresentation (politics)Plan (archaeology)Mathematics educationPsychologyVisual artsSociologyComputer scienceArtSound (geography)CommunicationGeography
DOInot available

Abstract

fetched live from OpenAlex

This teacher/action-research inquiry investigated awareness and understanding about students’ sense of place (community) through arts-based lessons within a classroom ethnography framework. Two Teacher Candidates used social constructivist pedagogy to plan and teach the same lessons to two groups of elementary students in two different locales, Kamloops (small city) and Ashcroft (rural). Soundscapes, visual imagery maps, role play and reflective writing were the aesthetic media utilized. Interpretation of the data collected (video, audio, observation and field notes, class discussion and informal teacher-student and student-student conversation) were developed and created using autobiographical, reflective narratives by the teacher-researchers involved. Findings included: (1) shared creative experiences utilizing acoustic awareness and the use of aural representation as a way of expressing understanding was a new and effective learning tool for students in this study; (2) sounds and images, as concrete representations of reality as well as symbolic

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0030.009
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.203
GPT teacher head0.461
Teacher spread0.258 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2008
Admission routes1
Has abstractyes

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