Discussing moral goods and confronting research fetish: Review of “Fundamentals of research on culture and psychology: Theory and methods”
Bibliographic record
Abstract
We review Valery Chirkov’s “Fundamentals of research on culture and psychology: Theory and methods.” The book is written as a textbook, but clearly takes a position that work in culture and psychology should be “problem-oriented, realist, and case-based” (p. 299). It is an innovative piece that covers philosophical paradigms, planning research, and conducting research. Our review outlines main claims made by the book that are likely provocative to mainstream variable-based research and ones that will likely challenge cultural psychologists. Despite the provocations, we argue that the book is an excellent place to start because, as illustrated through the work of Charles Taylor, Chirkov insinuates generative conversations about moral goods. A complimentary discussion through the purview Slavoj Žižec shows how Chirkov promotes awareness of a potential fetish with research methods that are counter productive and unethical.
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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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.014 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".