(Re)Imagining Inclusion: Community-Based Art Project to Create an Environment for Immigrant Artists.
Bibliographic record
Abstract
Art, community, and immigration programs encourage participation in the cultural life and support local people in the development of interconnectedness. Community art and immigrant art projects have been used to get artists, educator, students, local ethnic and communities as well as with marginalized groups and minorities. This helps the researchers to generate new practices for developing provincial level and observe federal level community-based identity for newcomers, immigrants, and refugees their lives in a new country as a host culture. The emerging question is “Does art have the power to evoke change individually and/or collectively?” This topic has been discussed by many discourses, theorists, artists, scholars over the past three decades. The contest is how aesthetic forms engage, challenge, counter the social, cultural, and political conditions of society by scholars, artist, and citizens. At this point, arts-informed scholarship has become important vehicle for these kinds of questions to be explored. As an artist scholar and artist educator, I believe that contemporary art can offer hope and has potentiality for social activists, educators, and cultural workers worldwide. Consequently, my educational research project focuses on community and arts-based projects through thinking how community-based and artmaking can transform and contribute social change by working artists and makers form underrepresented immigrant groups and communities. Working with Contemporary Calgary and public program YYC/LRT public Program helped to develop such a project focusing on Calgary-based racialized immigrant women artists. Immigrants, in fact, through the economic and social conditions (both distance and detachments) they became linked to the different possible positions in social space (that is) as a new and host culture in Calgary.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.019 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".