Bibliographic record
Abstract
In this issue, as with many general issues of JTL, we bring a diverse collection of papers from scholars-new, emerging, and established-on a range of topics and issues.We begin with a discussion of how higher education might be re-imagined to better meet the needs of today's students.We then delve into teachers' mental health during COVID-19 for a discussion of how stress and depression played out differently and similarly by gender during the pandemic.Two articles focus on teaching practice.One introduces the 'Tricky Pickle,' by exploring reading instruction in play-based kindergarten programs as a balancing act between the competing demands of stakeholders and the varied needs of young learners.Another talks about the opportunities for secondary pre-service teachers to experience productive struggle in the teaching of mathematics We conclude with two articles that speak to the interplay of teaching and equity, diversity, inclusion, and decolonization.For post-secondary educational institutions to better meet contemporary student needs, foster student mental health, and create interdisciplinary life-long learners who are prepared for the ever-changing workforce, fundamental institutional change is needed.Rebecca Collins-Nelsen, Michaela Hill, and John Maclachlan suggest changes that centre on the relationships among time, learning, and risk that consider a greater commitment to year-round learning, innovative courses that encompass various lengths, and an increase in 'low-risk' learning opportunities.Teaching has long been known to be a stressful job that often results in high burnout and teacher turnover.Andrea Huseth-Zosel, Sarah Crary, and Megan Orr conducted a quantitative study to explore the impact of changes in teaching modalities resulting from the COVID-19 pandemic on the mental health of K-12 teachers, by gender, during the first year of the pandemic.Findings suggest that female teachers were more likely to experience higher levels of stress than male teachers, while male teachers were more likely to experience higher levels of depression than female teachers.Further, physical symptoms were more likely to be experienced by female teachers.While the value of play in learning for young children has been recognized for many years, challenges have arisen in teaching young children to read in play-based learning kindergarten classrooms.Yvonne Messenger and Tiffany Gallagher present a mixed-methods study that provided context and explored kindergarten educators' experiences, self-identified strengths and challenges to teach reading within play-based programs, and their goals for continued growth pedagogical-content knowledge.Findings suggest the need for researchers to engage in more
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".