Fieldwork in the Era of Social Media: Opportunities and Challenges
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
Abstract Social networking sites have recently garnered academic attention for their role in fostering democracy and openness in both developed and developing regions. Unfortunately, in political science, this newfound interest has not yet translated into a greater interest in social media as a methodological tool for researchers conducting fieldwork. How has the era of social media influenced the way political scientists conduct their fieldwork? How can researchers make the most of the opportunities offered by social networking sites while abiding by the strict standards of their ethics board? This article highlights the potential in social networking sites for recruiting participants and gathering data and looks at the impact sites such as Facebook have had on building and maintaining trust with research participants. In contrast, it explores how social media may compromise one's ability to uphold the “do no harm” principle guiding all academic research by jeopardizing participants' confidentiality and anonymity, a risk deemed especially high for vulnerable populations or sensitive regions. Insight gleaned from the researcher's own fieldwork in two minority provinces of Indonesia in 2010–2011 is used as a case in point.
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 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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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