Teeters, (Taught)ers, and Dangling Suspended Moments: Phenomenologically Orienting to the Moment(um) of Pedagogy
Bibliographic record
Abstract
My intention in writing this article is to illustrate how I engage with the process of orienting to the meaning of pedagogy by inquiring into several moments in my life where I am able to fully experience its (moment)um. I begin this phenomenological inquiry by plunging into my experience on a teeter-totter as a young child, and use the sense of ups and downs as a metaphor for the tensions of weight and weightlessness, comfort and challenge that characterize the pedagogical world. I then attempt to gain a more perceptual understanding of pedagogy by narrowing in on the suspended moment, which becomes a metaphor for the pedagogical moments of support, vulnerability, and opening that emanate from this tension. In these particular moments, I am able to dwell in the spaces in-between my everyday ups and downs and become existentially conscious and pedagogically connected to the world around me. By metaphorically connecting each of these moments to my teeter-totter experience, I illustrate how embracing the tensions of life and allowing myself to dwell in a suspended moment, deepens my perceptual understanding of pedagogy and influences my current pedagogical practice as a new teacher and master’s student.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".