New metaphors about culture: Implications for research in science teacher preparation
Bibliographic record
Abstract
Abstract Culture has been commonly used in science education research, in particular to examine issues of equity for students from low‐income, racial, and ethnic minority communities. It has provided a lens with which to appreciate science classrooms as cultural places and to recognize the importance of students' cultural ways of being as resources for science learning. Scanning the ways that “culture” has been used in recent publications shows that much science education research continues to draw from an older view of culture(s) as a bounded and coherent set of beliefs and practices associated with a distinct social world, referred to as a pluralizable or discontinuous view of culture. This view of culture has been critiqued on the basis of its assumptions of homogeneity of groups and as masking the role of systemic inequity in the marginalization of people from certain communities. This view of culture is often associated with a particular set of metaphors, such as cultural borders, gaps, mismatch, conflict, and tension. Despite increasing attention in science education research to an alternative view of culture as porous and emergent, these newer ways of thinking about culture do not yet seem to have been taken up in research around science teacher preparation. Recognizing the usefulness as well as the limits of the older view of culture as bounded and coherent social worlds, this paper points to other metaphors about culture—such as funds of knowledge, third space, and figured world—that might be more helpful in preparing science teachers. By exploring the metaphors we use to think about culture and how they structure the inferences and actions of teachers and researchers alike, we can envision new avenues of research and practice that will inform the preparation of science teachers for the complexity of our schools and classrooms. © 2012 Wiley Periodicals, Inc. J Res Sci Teach 50:104–121, 2013
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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 | 0.040 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.013 | 0.093 |
| Scholarly communication | 0.019 | 0.051 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.007 | 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".