How Does Intercultural Competence (IC) Manifest Within the Community Network of MT Space?
Bibliographic record
Abstract
Intercultural Competence (IC) is a term (among a myriad of similar terms) used to describe the ability to contribute to “…improving human interactions across difference, whether within a society (differences due to age, gender, religion, socio-economic status, political affiliation, ethnicity, and so on) or across borders” (Deardorff, 2019, p.5). From a developmental perspective, this capacity can be described by certain attitudes, conditions and capabilities along a continuum of expertise. By examining relationship patterns through the lens of Bennett’s Developmental Measure of Intercultural Sensitivity (DMIS), and applying Hammer’s psychometric measurement tool, the Intercultural Development Inventory (IDI), this inquiry takes a close look at the collective which encircles a renowned professional theatre company that is dedicated to intercultural practices and social justice-oriented community engagement in Canada. This qualitative constructivist approach examines how IC was apparent within the social network of MT Space during their 2019-20 artistic season.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".