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Record W1541149953

CO-CREATING SPACES: A NARRATIVE INQUIRY INTO BELONGING, IDENTITY, AND CURRICULUM MAKING WITHIN SCHOOLS

2012· dissertation· en· W1541149953 on OpenAlexfundno aff
Tara Lynn Prystay-Thiessen

Bibliographic record

VenueoURspace (University of Regina) · 2012
Typedissertation
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
FundersUniversity of Regina
KeywordsIdentity (music)CurriculumNarrativeNarrative inquiryPedagogyMathematics educationSociologyPsychologyArtAestheticsLiterature
DOInot available

Abstract

fetched live from OpenAlex

This narrative inquiry (Clandinin & Connelly, 2000) inquires into the lives of three teachers, Anne-Marie, Lucy, and me. As three co-researchers we inquired into our stories of experiences which we lived out as children and youth as we participated in art making spaces in school. Throughout our research conversations we shared artistic representations of our experiences. Each of these conversations was audio taped and highlighted tensions we experienced in schools. This unfolding sharing of our stories of experiences led Anne-Marie, Lucy, and me to create visual art pieces that represented the vital place of art making experiences and spaces as we negotiated diverse school contexts. I drew upon both our research conversations and our artistic representations to compose this thesis which highlights art-making experiences as central in shaping a curriculum of belonging in schools. All aspects of this narrative inquiry were negotiated with Anne-Marie and Lucy.

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)0.006
metaresearch head score (Gemma)0.008
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0120.027
Scholarly communication0.0110.012
Open science0.0010.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.283
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
Published2012
Admission routes1
Has abstractyes

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