Trust and its Consequences: A Regional Senior Manager's Experiences of Meaning Making in the Canadian Public Service
Bibliographic record
Abstract
This thesis explores the role of trust in meaning making in the Canadian Federal Government from the perspective of a senior manager based in regional operations. I take a pragmatic approach to my research, using the methodology of reflexive narrative to inquire into my experiences in this role. This method includes reliance on a community of inquirers to validate the research. In this thesis, I take a highly social view of trust, exploring it from a perspective that assumes that all human relating is complex and responsive. I propose an understanding of trust as a paradoxical and emergent patterning of human relating. Trust organises our experience of being together in the living present, and is simultaneously experienced individually and thus particularised, while being socially constructed and generalised, at the same time. It arises between interdependent people trying to get things done together. Whereas an idealised understanding of trust would claim that it makes the work easier, in this thesis I argue for a more nuanced and complex position: that trust can both enable and constrain us in our work to make meaning. I point to the potentially destabilising nature of collective meaning making, as it often occurs because of a breakdown or disruption of expectations, which challenges our beliefs, values and identities and can be experienced as conflictual. Patterns of trust relationships may enable our work by supporting the collective exploration of difference and negotiation of meaning by allowing us to stay in relation with each other in a good enough holding of our anxiety. Strong patterns of trust relations can also be constraining where strong we-identities and cult values (a term pragmatist G.H. Mead used to refer to social patterns present in actions as generalisations and/or idealisations (Stacey and Mowles, 2016, p. 365)) lead individuals and groups to rely on and trust those colleagues whom they believe think like they do, to the exclusion of others. I further argue that the use of quantitative methods in our meaning making is paradoxical in two ways. First, quantification is trusted as a source of objective information despite already being a product of our social relating to each other. Second, reliance on metrics can be potentially destructive of trusting relationships in our work to make meaning together, as it discounts practical knowledge and judgement, which may in turn further strengthen our trust in and reliance on quantitative information. I propose the concept of buffering conversations to refer to the often one-on-one conversations held outside of formal meetings, which are used to explain or soften interventions in such meetings and to negotiate, repair or maintain relationships and expectations as we continually negotiate our understanding of whether we can trust each other. I contribute to an understanding of trust within a large, distributed, national public sector organisation where, because of distance and geography, face-to-face trusting relationships are difficult to build and maintain. I also identify changes to my practice, which have resulted from my inquiry into trust.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".