A Typology of Organizational Membership: Understanding Different Membership Relationships Through the Lens of Social Exchange
Bibliographic record
Abstract
Using a social exchange perspective and responding to prior calls to separate resources exchanged from the relationship between parties, we develop a relationship typology based on rights and responsibilities arguments. We begin with the idea that various levels and types of rights and responsibilities are the exchange currency utilized by the employer and employee, respectively. Further, the degree to which an organization grants rights to an individual and the degree to which the individual voluntarily accepts responsibilities results in four distinct organizational membership profiles (i.e., peripheral, associate, detached, and full). We believe this membership typology is an important theoretical mechanism that may be used to link the exchange between the employee and employer (as represented by psychological contracts) to psychological attachment (as represented by perceived membership) between these two parties. Specifically, members in each profile will tend to have certain kinds of psychological attachments to the organization, causing them to (i) perceive membership in certain ways and (ii) behave in a manner consistent with that perception. The article concludes by discussing the implications of the propositions for both researchers and practitioners, as well as making suggestions for future research efforts.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".