Bibliographic record
Abstract
Purpose – The purpose of this paper is to provide a summary of key aspects of a recently defended PhD thesis. It enables readers who may be interested in the thesis topic to gain an overview of that work and a link to the entire thesis through a URL link www.dropbox.com/s/1gikjlh6qw0v26u/Dissertation_Eduardo_Lopez_03122015.pdf?dl=0 . The second purpose of this Thesis Research Note (TRN) is to explain the thesis author’s doctoral journey. Design/methodology/approach – The methodology was rooted in critical realism using mixed research methods. The approach for the paper is to provide a reflective narrative to explain the lived experience of the authors throughout the candidate’s doctoral journey. Findings – The theoretical implications of this study are the introduction of two new constructs (The Small Sins Allowed (SSA) and the Line of Impunity (LoI)) and the definition of these constructs as variables that affect corporate governance. Research limitations/implications – Although this study was intended to collect feedback regardless of geographical location, over 91 percent of responses came from the USA, Canada, and Latin America. For this reason, generalization beyond these boundaries requires further analysis. Practical implications – The practical implications are related to the application of the two constructs (SSA and the LoI) into the daily corporate governance activities. Social implications – SSA and LoI, can be the foundation for renewed and vigorous corporate governance. SSA helps to establish a level above which adherence to ethical standards is expected. LoI aids in identifying ethical fault lines. Together they help to keep unethical behaviors under control. Originality/value – The TRN provides a highly individualized account of a doctoral journey but it is intended to contribute to the growing body of TRNs published in this journal that in turn may inform decisions relating to candidates embarking on a doctoral journey.
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 | 0.017 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".