Connection in Unexpected Places: How, Why, and With What Consequences Workers Connect with Clients
Bibliographic record
Abstract
Research on connections in the workplace has investigated many different types of relationships. However, less attention has been paid to one type of relationship that is a vital component of many workplaces: the relationship between the worker and the people they provide goods or services to (e.g., clients, patients, or audience members). Importantly, insights from broader social science scholarship suggest that the process of forging connections with clients is likely different from forging relationships with coworkers or mentors. In an effort to gain greater insight into worker-client connections, we invited a set of scholars studying this phenomenon within organizations. We have deliberately assembled a collection of qualitative studies that draw on findings from interviews, participant observation, and ethnographic techniques to develop rich, deeply descriptive, and contextual insights from a variety of workplace contexts, investigating how, why, and with what consequences people work with the clients of their organizations. How and Why Social Workers Establish Relational Boundaries with their Clients Author: Solomiya Draga; U. of Toronto Author: Marlys K. Christianson; U. of Toronto Resolving Misfit through Embodiment Work in Specialized Job Coaching Author: Ann-Sophie Baeken; KU Leuven Author: Emily Dunham Heaphy; U. of Massachusetts, Amherst Author: Anneleen Forrier; KU Leuven Author: Nele De Cuyper; KU Leuven How Prosocial Professionals Approach Client Status and Expert Power Author: Lakshmi Ramarajan; Harvard U. Author: Julie Yen; Harvard Business School Simplicity on the Other Side of Historical Complexity Author: Jeff Thompson; Brigham Young U. Author: Lyndon Earl Garrett; Boston College Author: Mac Jeffrey Alexander Strachan; - Author: Stuart Bunderson; Wash U.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.014 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.003 |
| 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".