Bibliographic record
Abstract
Purpose This paper seeks to examine how auditors sought to establish their trustworthiness as trust providers on the internet; a vision which has remained largely unrealized. The investigation focuses on the WebTrust assurance project, launched by the North American accounting institutes to reinvigorate the alleged declining market for the expertise of external auditors. Design/methodology/approach An in‐depth longitudinal case study drew on a social theory of trust to examine the complexity of relations upon which trustworthiness of professional claims is predicated and investigate how commercialism has influenced the development of WebTrust. Findings Analysis illustrates the critical role that experts have in professionalization processes in trusting (or not) their own systems of expertise. Also, face‐to‐face relationships continue to play a key role in establishing the trustworthiness of professionals and their systems of expertise – even in the cyberspace domain. Practical implications It is argued that the WebTrust case and other commercialistic ventures sustained in accountancy provide a persuasive argument against the benefits of the free‐market logic in professional domains. Professional associations should be more vigorous in defending professionalism. Originality/value The research indicates that élite bodies of the profession, including professional associations, conceived of WebTrust mainly through a commercialistic lens – which is particularly revealing of the mindset that seemed to characterize a number of experienced professional accountants across North America shortly before the collapse of Andersen. The WebTrust saga illustrates how the profession has strayed from its ideals, or myths, of service ethic towards more focused efforts in developing “innovative” services based on a commercialistic logic.
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.
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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".