Calling for a Shared Understanding of Sampling Terminology in Qualitative Research
Bibliographic record
Abstract
In this article we present the critical analysis of a recent methods overview, authored by McCrae and Purssell, as a means to highlight and address several important ambiguities and misunderstandings associated with terminology commonly used to describe sampling in qualitative research. We share several definitive understandings of sampling-related issues, which have been informed by a rigorous analysis of the methods literature from another earlier methods overview focused more broadly on sampling in qualitative research. Specifically, we address ambiguities and inconsistencies related to what can be sampled in qualitative research (the sampling unit), the concept of theoretical sampling, the term purposeful sampling, the appropriateness of initial sampling in grounded theory, and the need to distinguish between the functions of reporting one’s sampling methods and describing the final participant sample. Finally, we argue that a continued lack of clarity in the language we use to describe what we do erodes the real and perceived quality of qualitative research. We point to the important role of methods overviews both for focusing attention on underdeveloped research methods topics and as a source of solutions to methodological problems.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Qualitative | medium |
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 | 0.672 | 0.647 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.016 | 0.075 |
| Scholarly communication | 0.023 | 0.043 |
| Open science | 0.010 | 0.028 |
| Research integrity | 0.012 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".