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Record W3215010284 · doi:10.1287/orsc.2021.1514

Seeking Purity, Avoiding Pollution: Strategies for Moral Career Building

2021· article· en· W3215010284 on OpenAlex
Erin Marie Reid, Lakshmi Ramarajan

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOrganization Science · 2021
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsMcMaster University
Fundersnot available
KeywordsConstruct (python library)SociologyInstitutionMoral disengagementProcess (computing)Good moral characterPublic relationsSocial psychologyPsychologyPolitical scienceSocial scienceComputer science

Abstract

fetched live from OpenAlex

This study builds theory on how people construct moral careers. Analyzing interviews with 102 journalists, we show how people build moral careers by seeking jobs that allow them to fulfill both the institution’s moral obligations and their own material aims. We theorize a process model that traces three common moral claiming strategies that people use over time: conventional, supplemental, and reoriented. Using these strategies, people accept or alter purity and pollution rules, identify appropriate jobs, and orient themselves to specific audiences for validation of their moral claims. People’s careers are punctuated by reckonings that cause them to reconsider how their strategies fulfill their moral and material aims. Experiences of gender and racial discrimination, access to alternate occupational identities, and timing of entry into the occupation also shape people’s movement between strategies. Over time, people combine these moral claiming strategies in different ways such that varying moral careers emerge within the same occupation. Overall, our study shows how people can build moral careers by actively revising purity and pollution rules while holding fast to institutional moral obligations. By theorizing careers as an ongoing series of moral claiming strategies, this research contributes novel ideas about how morals weave through and organize relationships between people, careers, and institutions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.721
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.007
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.257
GPT teacher head0.422
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it