Bibliographic record
Abstract
Scholars have been calling for the integration of the natural environment within social work for over thirty years. However, the literature provides little insight into youth perspectives on their relationships with land and place, particularly in rural and remote communities. In fall 2022, I interviewed twelve students ages 14-17 at Fort St James Secondary School in BC’s Nechako Lakes District (School District 91) about their experiences spending time outdoors. By student choice, half of these interviews took place inside their school and half took place in outdoor settings nearby the school. Through reflexive thematic analysis, I developed five themes from our interviews, including (1) Specificity in relationships: Where we are (and who we are) matters; (2) Pathways to negotiating relationships with land and place; (3) Intersections of community, land, and youth resilience; (4) People are connected through place and time; and (5) Youth have agency and responsibility. My discussion links youth relationships with land and place to social work practice and highlights connections between the resilience of youth, their communities, and the land and water they rely on. This research contributes to a growing body of literature on social work and the environment and identifies future avenues for the integration of land and place within research.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".