Evaluation of Experiences in the Canadian Conservation Corps: A Qualitative Content Analysis
Bibliographic record
Abstract
A qualitative content analysis study was conducted in partnership with the Canadian Wildlife Federation (CWF) and Mitacs to explore the experiences of participants involved in the Canadian Conservation Corps (CCC) program. 27 semi-structured interviews conducted with 14 interviewees were audio-recorded and transcribed. Interview data were analyzed using an inductive qualitative content analysis of latent data. The analysis identified seven themes which are: Theme 1: Participants Discussed the Importance of Community Theme 2: Participants Learned Through Difficulty Theme 3: Participants Experienced Personal Growth Theme 4: Participants Developed a Range of Skills Theme 5: The CCC Supported Participants’ Career Development Theme 6: Stage 2 Leaders Described Benefits to Their Organizations Theme 7: Interviewees Offered Suggestions for Improvements to the CCC Findings were shared with CWF and stakeholders of the CCC to inform funders and to support future development of the program.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".