Assembling Jobs: A Model of How Tasks Are Bundled Into and Across Jobs
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How are tasks bundled into and across jobs within organizations? In this paper, I develop a model of this process of job design by drawing on a multisite qualitative study of task allocation following the installation of a DNA sequencer. The model that emerges is one of the assembly of tasks through multiple subassembly processes with multiple assemblers. Four activities produced requirements and requests for job designs and propositions about how to meet these: actively searching, passively receiving, doing work, and invoking preexisting ideas. The ideas that emerge from these processes are further transformed through reconciliation, interpretation, and performance. My observations show that this overall process is far reaching and incorporates many elements, not all of which are explicitly intended for job designs. The arrangements that emerge from this process are not the product of a deliberate and controlled job design process within the boundaries of a single organization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it