ANNOTATED OUTLINE – SOCIAL CAPITAL
Bibliographic record
Abstract
1. The capital approach is an economic theory used to help measure and understand important features of the human environment. According to the Australian Bureau of Statistics (ABS), “Capital in economics is something produced in one time period to be used in the production of other goods and income during future time periods ” (ABS, 2004, p.109). The four primary forms of capital currently are natural, economic, human and social. Of these, the most controversial is social capital. 2. The Organisation for Economic Co-operation Development (OECD) defined social capital as the “ … resources gained through social ties, memberships of networks and sharing of norms” (Cotes and Healy, 2001, p. 23). This definition has since been adopted by several national statistical organisations, including the ABS and Statistics Canada. It implies that social capital exists to provide access to the resources of other capital forms. 3. In 2007, Czesany highlighted the importance of social connections when he defined social capital as the “Networks together with shared norms, values and understandings that facilitate co-operation within or among groups. ” This conceptualisation reflects recent acknowledgement that social capital is itself a unique and valuable source of well-being.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.251 | 0.093 |
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".