Canoe Trips: An Especially Good Place for Conversation About Student Transition
Bibliographic record
Abstract
Background: Many postsecondary institutions offer outdoor programs to incoming students as a form of orientation or transition event. Positive outcomes for students are shown to result from these interventions but less is known about the mechanisms leading to these outcomes. Purpose: This article argues that conversation is one of these mechanisms and suggests canoe trips are an especially good intervention in which to generate conversation about student transition. Methodology/Approach: Insights emerging from our own outdoor orientation program called Portage lead to a hypothesis that canoe trips create three conditions ideal for the generation of productive conversation about student transition: the emergence of communitas, more egalitarian and communal relationships, and a rich source of metaphor. Findings/Conclusions: The Portage experience shows promise as a way to help students explore their educational and transition experiences through conversation. Implications: The intentional generation of conversation through metaphor on canoe trips may offer a useful space of pedagogical possibility to help students contemplate and pass through their transition more productively.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".