The Use of Narrative Resources in a Career-counselling Course
Bibliographic record
Abstract
In this paper, we analyse the communication codes in two consecutive meetings of a postgraduate class on career counselling held at the Department of Philosophy-Pedagogy-Psychology of the University of Athens in winter semester of 2017. The basic idea in these meetings was to discuss real-world situations with the help of a teaching framework and short films produced within the context of a European project, called ‘Narrative Resources for Socio-Professional Inclusion’ (NARSPI). The dialogs that followed the presentations were analysed with the help a sociolinguistic framework known as ‘Legitimation Code Theory’ (LCT). The analysis showed that the verbal communication moved from the particularities of the videotaped stories to discipline-specific vocabularies. According to LCT proponents, such moves in the use of language create wavelike forms of communication codes based on different levels of semantic gravity and semantic density. Such ‘sematic waves’ allow new ideas to be integrated into existing ideas and finally legitimise membership and scholarship in an academic field.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".