Chercher ses origines sur Facebook : quels liens entre les médias sociaux et la quête des origines en adoption internationale ?
Bibliographic record
Abstract
Research Framework: Internationally adopted people are gradually using more social media tools to search and find their biological family. Biological families are also using these tools to find children put up for adoption. This article aims to present the ways in which virtual contact with the biological family in international adoption influences adult adoptees’ search and reunion. Objectives: This study aims to understand the experiences and perspectives of internationally adopted adults in regard to their digital contact with their biological families. Methodology: The data presented in this article come from a qualitative study centered around eight Quebec internationally adopted adults. They participated in semi-directed interviews about their experience of a virtual contact with their biological family. Data collected were analyzed through an interpretative phenomenological analysis.Results: Through their discourse, the study reveals that participants award great importance to their origins. Interest in their origins motivated them to find their birth family through social media or to respond to contact initiated by their biological family. Participants wish to know more about who they are and where they come from. However, not all participants believe that searching for their origins is a mandatory step for adoptees. Conclusions: The notion of origins is omnipresent throughout the lives of the participants. Social media allows them to discover who they are and to learn about their history and their birth family. Contribution: The results of the study show the impact of social media on the search for origins in a context where digital contact with the biological family is more and more frequent in the journey of international adoptees.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".