Bibliographic record
Abstract
I imagine mathematics to be a place of loving kindness and capability. Loving kindness is a way of being together, one that affords and sustains capability; and making the (math) classroom a place of loving kindness consists in taking an active interest in one other. Nussbaum (2011) characterizes capability as an answer to the following question: “What is each person able to do and to be?” (p. 18). Drawing on Nussbaum’s (2011) capabilities approach as a broad, normative framework for characterizing individual well-being in the context of teaching and learning, I inquire into my experience teaching a mathematics class in which we cooperatively built 14-foot Prospector canoes. I explore the potential for a hermeneutic pedagogy as a means to both interpret and cultivate capability, and to identify three specific, significant capabilities that emerged in our work together—autonomy, affiliation and hermeneutic imagination—as valuable in and of themselves, yet also essential to cultivating and securing additional capabilities, and to furnishing a space for loving kindness in the mathematics classroom.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".