Reflexivity in nonprofit management research: A reflection on the role of self as researcher
Bibliographic record
Abstract
Abstract Drawing on three diverse case studies, the research note illustrates the use of reflexivity as an advantageous research strategy and its implications for nonprofit management and leadership research. Reflexivity is both a product and a process, that highlights a mutuality between researcher and participants in creating collaborative knowledge through intentional information exchange. For nonprofit organizations, reflexivity offers a research method that extends the sector's community‐based participatory approach. On the surface, nonprofit organizations are comfortable with diverse research methodologies. The multifaceted systems, interactions and processes that characterize nonprofit organizations require researchers to incorporate standard methodologies alongside more complex dimensions of participants' lived experiences. This paper highlights why reflexivity is a viable social constructivist research method relevant to the nonprofit management research collaborative approach.
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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 | 0.278 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.024 | 0.164 |
| Scholarly communication | 0.034 | 0.037 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.014 | 0.027 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".