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Record W3171337915 · doi:10.28945/4742

Toward Engaging Difference in a Globalized World

2021· article· en· W3171337915 on OpenAlexaffabout
Jennifer MacDonald, Jingzhou Liu, Sylvie Roy, Jody Dennis, Stefan Rothschuh, Marlon Simmons

Bibliographic record

VenueInternational journal of doctoral studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMeaning (existential)Context (archaeology)SociologyPedagogyBeijingDelegationDiversity (politics)GlobalizationChinaRelation (database)Identity (music)PsychologyPolitical scienceAesthetics

Abstract

fetched live from OpenAlex

Aim/Purpose: This paper reflects on participation in an International Doctoral Research Seminar, held in Beijing, China, to consider what it means to locate difference and make meaning in a globalized world in relation to teaching and learning. Background: The impetus for our inquiry stems from our shared experience at the seminar, which brought together 12 graduate students and six faculty members from three universities. We came with diverse life stories, educational and professional experiences, and research interests. Alongside presentations and school visits, some students questioned how teaching and learning practices differ in China compared to their experiences in Canada. Methodology: We employ an interpretive approach which allows us to revisit our individual stories and to explore different views of meaning-making in a globalized context. Specifically, two authors, positioned by different backgrounds (Chinese and Canadian), share their life histories and experiences for wider dialogue with other delegation members. We consider their experiences at various levels of education (K-12, leading up to graduate school, and at the doctoral seminar) as a mode of generating dialogue around the different contexts in relation to teaching and learning. Contribution: Our article contributes to the area of globalizing teaching and learning. We invite students and educators to revisit their lived experiences and advocate for daily practices that might defy sameness caused by the forces of globalization to instead contribute to epistemological diversity and tolerance. Findings: Through the process of unpacking the lived experiences of the two authors, we encounter the complexities of already being products of a globalized world. We reveal how a singular normative mode of knowing is perpetuated in many educational institutions. Difference, however, was located in the nuances of our stories. Thus, cultivating a practice of paying attention to the dynamic forms of knowing as they emerge can be a process of unlearning sameness toward rich meaning-making. Recommendations for Practitioners: We challenge educational practitioners to reflect on the ways in which meaning is, and can be, generated to resist uniformity and honor the lived experiences of students. We offer an opening to engage in narrative opportunities to promote dialogue and facilitate collaboration. Recommendation for Researchers: We open possibilities to consider a different ethic for generating meaning that resists overpowering global powers and honor local knowledge. Impact on Society: Our article provides an interpretive lens of global meaning-making to discuss critical social, cultural, and ecological dilemmas facing humanity through individuals’ narratives and life histories. Future Research: Future research will inquire into practical and ethical considerations that might play out in local settings (lectures, seminars, assessments, research proposals) and global collaborations, such as future doctoral seminars, to confront western exclusivity.

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)0.023
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.023
Threshold uncertainty score0.121

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0170.086
Scholarly communication0.0230.020
Open science0.0030.030
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.343
GPT teacher head0.490
Teacher spread0.147 · 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 designTheoretical or conceptual
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

Citations3
Published2021
Admission routes2
Has abstractyes

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