Ethics in the Age of Technological Change and its Impact on the Professional Identity of Librarians
Bibliographic record
Abstract
Professional ethics and core values provide professionals with guidance for their actions by helping professionals determine what constitutes right and wrong professional action. Because they are written for and by librarians, these documents offer one articulation of librarians' professional identities. This chapter examines the core values of librarianship with an eye to how they articulate the relationship librarians have with technology. These documents illustrate that librarians understand technology to be a tool that is used to meet the information needs of users. The Social Construction Of Technology (SCOT) is discussed as an alternative approach to the understanding of technology by LIS professionals. SCOT examines the social processes that are behind the development of technologies and highlights how different social groups contribute to the social meaning and even use of technology. SCOT provides an expanded view of ethics that encourages librarians to not only consider their professional ethics when implementing a new technology but also the intentions of the technology's developers, its various users, and their local communities. To illustrate the potential of SCOT for librarians, this chapter explores an examination of how librarians have managed the ethical challenges that Radio Frequency Identification (RFID) has brought to library services, followed by an examination of how librarians interpret their ethical role as service providers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.034 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".