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Record W2729978886

Learning in the Third Age: A Look into the Community Art Studio

2017· dissertation· en· W2729978886 on OpenAlexaboutno aff
Nicole Macoretta

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2017
Typedissertation
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningExperiential learningPsychologyStudioPerceptionEmpowermentAutonomyInformal learningVisual artsPedagogyArt
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study investigated the perception of learning by third age participants at an unprogrammed community art studio (Timm-Bottos, 1995) in Montreal known as an ‘art hive’ (Timm-Bottos, 2012). Third agers are defined as participants between the ages of 55-75 (Laslett, 1989), and participation is defined as making art. A case study research design was used, and 11 participants in the third age at the art hive known as ‘La Ruche d’Art: St Henri’ were interviewed about their learning experiences. Emergent themes suggested learning was heavily influenced by the structure and facilitation, as well as the social aspect of the art hive. Perceived learning included instrumental skills such as artistic skills, techniques, and social skills. Embodied and transformative learning experiences included learning how to freely express oneself, learning essential meanings and life lessons, learning new or broadened perspectives, and learning the healing power of art making. Learning was perceived to occur simultaneously by observing others and through self-initiated and directed processes. Many of the reported learning experiences were perceived as transformational, and led to experiences of personal growth, empowerment and profound fulfillment. This study points to many implications for the art hives and other community art studios to have a significant impact on the well-being of aging populations, as they offer opportunities for participants to express themselves creatively, build self-efficacy and autonomy, as well as feel welcomed to belong to an inclusive, loving community.

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)0.005
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.011
Scholarly communication0.0050.004
Open science0.0020.007
Research integrity0.0020.004
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 head0.061
GPT teacher head0.374
Teacher spread0.313 · 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
Published2017
Admission routes1
Has abstractyes

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