Becoming and Being a Camp Counsellor: a study of discourse, power relations and emotion
Bibliographic record
Abstract
This study problematises current knowledge of camp employment in order to explore the role of emotions in both positive and negative experiences of camp counsellors. Young camp counsellors and management staff are reconceptualised in post-structuralist terms, that is, they are selves that are multiple and fragmented, engaged in everyday experiences and interactions, and constituted in discourse and practice (Marshall, 1997). Camp counsellors are situated in a nexus of power relations with campers, peers, camp management and their own self. Just how they negotiate these power relations is central to my study. In this way, a post-structuralist perspective informs a dynamic and deeper understanding of how power is at work in shaping the emotion work of camp counsellors. Thus I bring Foucault’s notion of power together with the sociology of emotions and emotion work. A reflexive methodology guided the design, data collection, analysis and writing of my research. After completing two pilot interviews, I conducted thirty-eight in-depth interviews during the fall of 2009 in Ontario, Canada. Interviews were transcribed and were coded both manually and then again using NVivo software for more complex analysis. Additionally, I gathered field notes, five staff manuals, 51 web-published Mission Statements, various camp textbooks and one leadership program curriculum. The data was analysed for themes as well as discursive practices. Analysis continued throughout the writing process where I included a number of personal narratives of camp experiences.
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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.025 | 0.041 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".