Fundamental researcher attributes: Reflections on ways to facilitate participation in Community Psychology doctoral dissertation research
Bibliographic record
Abstract
As novice researchers, Community Psychology doctoral students encounter fresh challenges when they attempt to facilitate participation by members of the community in their dissertation projects. This article presents the merit in adopting fundamental researcher attributes, which have been described in published academic literature as personal characteristics that facilitate participation by members of the community in research studies. The value of these researcher attributes is exemplified in the discussion of one of the author’s experiences in the early stages of his dissertation research process. This article also presents new researcher attributes for facilitating participation by community members that the author recognised after critical reflection on his experiences during the same research process. Cultural humility, shared vulnerability, reflexivity, methodological flexibility, academic assiduity and creative resourcefulness are researcher attributes doctoral students should consider adopting and developing if they intend to facilitate participation by members of the community in their dissertation projects.Keywords: researcher attributes, graduate students, doctoral dissertation, participatory research, participation continuum
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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 | 0.107 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.027 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".