Community building in the MTBoS: Mathematics educators establishing value in resources exchanged in an online practitioner community
Bibliographic record
Abstract
Mathematics educators are engaging in an online community referred to as the Math Twitter Blogosphere (MTBoS) to support their practices. Although studies indicate that educators who participate in professional online communities engage primarily in sharing and consuming resources, and in some cases also in building and maintaining professional relationships, it is unclear how they interpret these opportunities. This study explores the community building activities mathematics educators refer to when speaking about their engagement in the MTBoS and unpacks ways in which they value and establish value in the activities they refer to. Findings indicate that members of the MTBoS community refer to identifying and selecting resources frequently, that they value resources that are inspiring, relevant, and reliable, and that they establish values through identifying resources with attributes of specificity, like-mindedness, credibility, and through repeated exposure over time.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".