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Record W3154033175 · doi:10.32920/ihtp.v1i1.1416

Two educators reflect on their immigration experience through creative writing

2021· article· en· W3154033175 on OpenAlexaffvenueabout
Jasna Schwind, Oi Ling Helen Kwok

Bibliographic record

VenueInternational Health Trends and Perspectives · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCritical Race Theory in Education
Canadian institutionsSeneca PolytechnicToronto Metropolitan University
Fundersnot available
KeywordsScholarshipImmigrationPedagogySociologyNarrativeValue (mathematics)Face (sociological concept)PsychologySocial sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Following Dewey’s philosophy of experience that all our life events inform how we evolve, both personally and professionally, two educators reflect on their immigration experiences. Being uprooted from one’s place of birth to another, at an oftentimes turbulent stage of development, young people face challenges in finding their sense of belonging. We engage in creative writing to reflect on our respective experiences of immigration to Canada to support our scholarship of teaching and learning. Using Dewey’s three criteria of experience: continuity, relationship, and situation, and Connelly and Clandinin’s Narrative inquiry self-study framework, we delve deeper into understanding how the transplantation from one continent to another continues to impact who we are today as persons and professionals. This critical reflection is of further value to us as educators, because we also want to gain a greater appreciation for our students’ experiences, most of whom have lived the stories of immigration. In this way, we hope to more effectively support and encourage our students, not only to survive, but to thrive in their new landscape. We trust our work will, likewise, be of service to educators worldwide who want to engage in their own inquiry of personally significant life events, and thus support the same in their students.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.543
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.496
Teacher spread0.427 · 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 teacher head, 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

Citations4
Published2021
Admission routes3
Has abstractyes

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