Autoethnography: Research as Reflection, Inclusion and Empowerment
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
Autoethnography is a personal, reflective, qualitative research method. It is obviously associated with anthropology, but may be more widely used in sociology and it occasionally appears in research in other social science fields. In this method, the researcher and the subject of research are the same person. It requires the researcher to engage in deep, rigorous, and reflective examination of their own experience and then to systematically analyze that reflection, drawing connections to theory, society, and culture as they do so. The resulting analyses can take many forms, including: scholarly prose, poetry, narrative, dialogue, and more. For the last year, we have been leading a learning community of librarians in the U.S. and Canada exploring the potential of this method to enrich the scholarly discourse in librarianship. Librarians in the community have committed themselves to collaboratively learning about the method, and each member is also producing an autoethnography of their own, exploring themes of identity and professional practice in librarianship. Most of the librarians in the learning community teach information literacy and it is increasingly clear that this method has a great deal to offer teaching librarians. Teaching librarians understand the importance of reflective thinking and metacognition in the learning process and there is a long tradition of reflective practice already in place in this community. Autoethnography is a method that busy, practicing librarians can do well and rigorously to inform their practice. Practicing professionals must make decisions quickly and in the moment as they draw on a body of practice knowledge gained through experience to do so. Donald Schön calls this “Reflection in Action.” Autoethnography offers a way to capture and share that practice knowledge that is so important in the classroom. It is also important to reflect on experience after the fact – Schön calls this “Reflection on action” – and autoethnography supports this as well. It pushes the researcher to connect their experience to something broader, to draw in theory, culture, and social factors, to make deeper meaning. Heidi Jacobs articulates the significance of this for librarians who teach information literacy: “Praxis – the interplay of theory and practice – is vital to information literacy since it simultaneously seeks to ground theoretical ideas into practicable activities and use experiential knowledge to rethink and re-envision theoretical concepts”. Autoethnography makes it possible for voices that get drowned out in large scale aggregations of data to be heard. It provides a way for the lived experiences of all librarians to be included in the professional conversation. It is an inclusive method and offers the potential to understand the role of information literacy in an inclusive society – as well as the inclusivity within the practice community itself. We will reflect in this paper on the experience of leading this learning community and share the insights we have gained about the potential of this method to inform the professional conversation about information literacy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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