Bibliographic record
Abstract
In this chapter, we examine what a relational ontology consists of, especially regarding questions of materiality, performativity and existence. In dialogue with Karl Weick’s notions of enactment, selection and retention, we show what this ontology has to tell us about this specific way of relating we call organizing and organization. Having defined the relational aspects of organizational processes, we also explore why disorganizing is always at stake when organizing takes place, creating tensions that constitute an intractable aspect of organizational processes. Studying dis/organization from a relational perspective indeed amounts to studying the communicative constitution of dis/organizing, that is, examining the ways things and persons get positioned or position themselves as organs or instruments by which others articulate themselves (in both senses of the word "articulate": assemble and speak), creating an agencement that can also disappear or be altered when contradictions or incompatibilities occur. It is the tensions inherent in these agencements that we especially focus on in the context of this chapter. This relational perspective is finally mobilized to analyze a meeting excerpt during which two managers and two human resource advisors speak about a workforce diversity program in a large Canadian organization.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".