Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With The Social Construction of What?, Ian Hacking aims to cool down the overheated debates around social constructionism (the 'science wars') by clarifying just what the phrase 'social construction' can be properly understood to mean. The book is a collection of previously published essays and lectures on a variety of topics, united not by a common argumentative thread but by this anti-polemical project. The first three chapters explore a series of approaches to specifying what is meant by the phrase 'social construction', and unpack the philosophical issues, or 'sticking points', raised by the application of social constructionism to the natural sciences. Chapters 4 and 5 develop the idea of 'interactive kinds', categories that interact with and alter the objects they label. Reframing social construction in terms of interactive kinds and looping effects helps to specify how a phenomenon can be socially constructed and real at the same time. Chapter 6 elaborates a distinction between 'forms of knowledge' and 'content of knowledge'. Hacking uses this distinction to assign relative roles to contingency and determinacy in the development of scientific knowledge. Chapter 7 applies the 'sticking points' developed in Chapter 3 to a case study of science-in-the-making, and Chapter 8 re-tells the story of the 'Captain Cook' controversy in a way that aims to defuse some of the tension. In this Review I will focus on Chapters 1-4, because these chapters introduce the concepts with which Hacking attempts to specify the meaning of 'social construction'; the later chapters are mostly applications of these concepts.
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.
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 | Science and technology studies Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | medium |
| gpt | Science and technology studies Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it