Making sense of plausibility : understanding the process of plausible meaning constructions : a case study of the New Brunswick Post-Secondary Education Commission
Bibliographic record
Abstract
When exploring the disaster at Mann Gulch, Weick wrote, "the phrase that holds the world together is, 'You know what I mean'" (1993, p. 632).During times of change, people strive to understand what is happening in a way that makes sense to them within their socially constructed environment.This thesis is a study in sensemaking that focuses on how plausible meanings are constructed, accepted and expressed.At its core, sensemaking is about understanding "how different meanings are assigned to the same event" (Helms Mills, Thurlow, & Mills, 2010, p. 183).This thesis builds upon the 'how' using a framework of sensemaking process, sensemaking properties, and linguistic structure, developed to unpack how people create meanings that have value, are instrumental and are actionableherein operationalized as functionally plausible.The location of study is a single case of proposed institutional reform of postsecondary education (PSE) in New Brunswick, Canada and the process of sensemaking is explored using the events of the case as a contextual location.Expressions of confusion and meaning creation captured in official reports, government documents and news media form the data of the case.The data is examined within a range of sensemaking ideas, bringing together the more recent work on sensemaking as a process (Weick, Sutcliffe, & Obstfeld, 2005) with earlier writings surrounding sensemaking as a set of properties (Weick, 1995).The data is analyzed through textual analysis (McKee, 2003) and the structure of language is studied as a medium through which meanings are created and expressed (Saussure, 1972).This thesis makes a number of contributions to our current knowledge.It refines the property of plausibility, pushing forward the importance of meanings that are functional.It uncovers the relationship of language within sensemaking, revealing the potential for multiple plausible meanings to exist, meanings that are attached to the same language symbols.It combines the multiple ideas around sensemaking, attempting to differentiate between the process of sensemaking and the constituent elements of sensemaking.Finally, it unpacks contextual pressures at play when sensemaking occurs both intra-organizationally and inter-organizationally.
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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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.044 | 0.054 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".