Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the theoretical foundations of the solidarity network concept and its perceived utility as an enabling force for social organizations to influence change. The theoretical framework presented is intended to stimulate dialogue, interest and investigation on the subject of solidarity networks. Design/methodology/approach The paper adopts a discourse analysis‐type approach to developing a theoretical framework for conceptualizing solidarity networks through an analytical review of existing literature on solidarity and solidarity networks. It is through consideration of this literature that the “threads” of a theoretical model for solidarity networks are “woven” together. Findings Based on the findings of the analysis the paper asserts that the following characteristics are among the defining elements of solidarity networks and help to form the basis of a theoretical framework that strives to create a more cohesive understanding and an applied exploration for future analytical investigations. These characteristics are: support for “broad” values, anti‐oppression and vision‐based solidarity for the future; the flexibility and adaptability of the network's organizational structure and issue‐area(s) of focus; that network members are motivated by a sense of mutuality, or mutual self‐interest; that network members are motivated by “high‐order” values associated with the “public good”; and that there is a demonstrated ethic of social responsibility and social justice. Originality/value The paper represents a theoretically‐based approach to conceptualizing solidarity networks. It adds new dimensions to one's thinking about social networks as a form of social relationship and social network analysis (SNA) as a “tool” for describing social relationships.
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.
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 | 0.019 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.038 |
| Scholarly communication | 0.013 | 0.024 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| 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".