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Record W4389222451 · doi:10.32920/ihtp.v3i3.1845

Pedagogy of Belonging: Pausing to be human in higher education

2023· article· en· W4389222451 on OpenAlexvenueno aff
Narelle Lemon

Bibliographic record

VenueInternational Health Trends and Perspectives · 2023
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumHumanityPedagogyFeelingContemplationNarrativeHigher educationSociologyPsychologyPolitical scienceSocial psychologyEpistemology

Abstract

fetched live from OpenAlex

Valuing care and self-care in higher education requires a conscious pause and rethinking of how we are together as educators and students. The pandemic caused various complexities, including changes in curriculum delivery, deadlines, and assessment modes, leading to feelings of overwhelm, anxiety, and change fatigue, which contributed to the emergence of panicgogy. This paper argues for the need to disrupt this way of being and experiencing the pandemic through valuing humanity and repositioning self-care and care by and for academics to inform their pedagogy. Presented is the narrative and the design story behind Pedagogy of Belonging (PoB), a systems informed framework that prioritizes relationships and humanizes teaching by placing students and educators at the center of curriculum and pedagogical decisions. PoB provides a pedagogical framework for progression throughout the teaching cycle. The paper suggests that PoB is a conscious pause, a contemplative practice that interrupts panicgogy, collective exhaustion, and disconnect in higher education. PoB repositions holistic education at the heart of what educators do, facilitating interconnectedness and encouraging a rethinking of care and self-care in higher education through the domain of belonging underpinned by relationships, engagement, and communication.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.220
GPT teacher head0.550
Teacher spread0.330 · 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.

Study designObservational
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
Published2023
Admission routes1
Has abstractyes

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