Examining the Relationship Between Expert Work and External Audiences
Bibliographic record
Abstract
This symposium investigates the interactions of experts and professionals with external audiences. This is an important theoretical and substantive issue- not least due to the proliferation of experts within organizations (Abbott, 1988; Freidson, 2001; Larson, 1977). Experts are used to exercising formal authority over their task domain, and resist external oversight over their jurisdiction by actors such as managers and regulators (Anteby, Chan, & DiBenigno, 2016). Yet, external audiences are key to the functioning, regulation, and development of expertise. Interfacing with external audiences is a core task for many professionals, such as lawyers, engineers and artists (Barley & Kunda, 2006; Becker, 1984; Sandefur, 2015). Further, in the absence of such external interfacing, expert groups can potentially fail to self-regulate (Huising & Silbey, 2013; Vaughan, 1997) and innovate (Baldwin & Von Hippel, 2011; Katila, Thatchenkery, Christensen, & Zenios, 2017) . Organizational scholars have paid much attention to the relationship between external audiences and experts within organizations (Pollock & Rindova, 2003; Uzzi & Lancaster, 2003; Zuckerman, 1999). However, empirical studies have typically examined expert-work as a means of explaining firm and market-level outcomes. Left undertheorized are the interactional bases of expert behavior, that is, how individual experts experience, make sense of, and navigate such outgroup interactions. For instance, how do we explain variation in expert reactions (affect, cognition) and responses (compliance, resistance, apathy) to oversight? Without an understanding of such interactional mechanisms, we risk missing the ‘other-side’ (Gray and Silbey 2011) of the expert-environment interface-that is, understanding how individuals ‘inhabit’ (Beth A. Bechky, 2011; Hallett, 2010) expert roles. Recent studies at the nexus of work, occupations and institutions highlight the importance and potential benefits of taking an interactionist view. In particular, scholars suggest that experts are socialized into ‘interaction orders’ (Fine & Hallett, 2014)- which entail specific emotion and sensemaking scripts (Creed, Hudson, Okhuysen, & Smith-Crowe, 2014; Hochschild, 2012; Voronov & Weber, 2016). Further, field studies point to the situated nature of such occupational scripts (B. A. Bechky & Chung, 2017; Chown, 2014). Research examining expert interactions with (or under the scrutiny of) external audiences provides an opportunity to meaningfully extend this growing body of scholarship. Indeed, interactions at the ingroup-outgroup interface can test (and breach) taken-for-granted norms, symbols and beliefs (“What Anyone Like Us Necessarily Knows”) – presenting particularly fertile ground for theory building that is well-grounded in the experiences and actions of workers. The Specter of Testifying: Forensic Scientists as Advocates for the Evidence Presenter: Beth Bechky; New York U. The Practices and Challenges of Inter-Organizational Knowledge Reuse Presenter: Andrew Nelson; U. of Oregon Relational Ruptures and the Shaping of Expertise: U.S. Puppeteers Move from Stage to Screen Presenter: Audrey Holm; Boston U. How to Tame an Expert: Examining the Role of Inter-Personal Interaction in Physician Error-Work Presenter: Kartikeya Bajpai; Northwestern Kellogg School of Management
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Management symposium on how experts and professionals (lawyers, engineers, artists) interface with external audiences; adjacent to the sociology of expertise but the object is professional work in organizations rather than research.
It examines expert work across professions, not research as a social or methodological system.
Organizational symposium on professionals facing external audiences; expertise in firms generally, not scientific research as the object.
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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".