Conceptual Commitments of Constructivism in an Age when Truth Matters
Bibliographic record
Abstract
The purpose of this special issue is to critically examine the constructivist moorings of contemporary developmental theory and practice, including the practice of research methods. This introduction to the special issue is intended to foreshadow the papers presented here by charting the terrain of several conceptual commitments that we consider paradigmatic cornerstones to constructivist approaches. Although constructivism has deep roots across disciplines in the sciences and humanities, generating a wealth of scholarship focused on its various assumptions and theoretical principles, here we target three: the active subject, normativity, and historicity. These principles are theoretically axiomatic of constructivist approaches, strongly interconnected, and highly relevant to some of the most pressing debates and challenges affecting contemporary science and society, not the least because they question fundamental notions that we often take for granted – notions as vital as the meanings of truth, fact, and objectivity. After presenting a primer on the meaning and significance of these three principles, we review their status as critical signposts for the work of scholars contributing to this special issue.
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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 | 0.034 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.075 |
| Scholarly communication | 0.026 | 0.032 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.009 | 0.029 |
| Insufficient payload (model declined to judge) | 0.005 | 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".