Evidentiality in science from specialization to popularization: A case study of COVID-19 texts

2.1.1 Evidential taxonomy

Evidential taxonomy is concerned with the following features (Table 1):

• – Sensory is a feature that construes propositional information as first-hand experience obtained through human sensory channels such as Vision, Audition, Gustation, Olfaction, and Tactus.

• – Reporting is a feature that identifies either an internal-oriented source (as in Self-reporting) or an external-oriented source (as in Other-reporting).

• – Inferring is a feature conveying not only inferences by which deduction and induction are acquired from perceived and intuited evidence, but also assumptions under which the inferential process is constructed on the basis of reasoning, assumptions, or general knowledge (Tang 2007: 68; Yang 2009: 91).

• – Belief is a feature construing information in terms of the text organizer’s mental state such as personal belief or opinion.

The typical realizations of these features are provided in Table 1 below. Each of the examples given is naturally occurring and retrieved from Corpus of Contemporary American English (abbr. COCA; Davies 2008).

2.1.2 Information source

Information source is a system representing the text producer’s evaluation of the warrantability of the source of a proposition; which presupposes a paradox that the text organizer is in fact responsible for every single word in his/her text. However, in scientific writing, most of the modal responsibility supposed to be assigned to Authorship is conventionally shifted to other semantic roles. These semantic roles are defined by the second and third-order features of this system. As a proposition is commonly referred to a Human source, its information can be construed in terms of diverse positionings. The options in information source cover but are not limited to the features listed in Table 2.

2.2.1 Modal responsibility

In terms of modalization (Halliday and Matthiessen 2014: 176–193), modal responsibility functions to construe how overtly the writer states his/her attitude towards the credibility of the given proposition (Thompson 2004: 67–75). In general, it can be realized as a textual deployment along the cline of subjectivity to objectivity (Table 3).

As the writer shows less of his/her subjectivity and more objectivity, so s/he takes less responsibility, and so the information contained in the proposition is more likely to be objectivized; while the writer shows more of his/her subjectivity and less objectivity, s/he takes more responsibility, and the propositional information is more likely to be subjectified. See Figure 3.

Figure 3:

The cline of objectivation.

Therefore, there is cline from subjectivation to objectivation in terms of the degree of responsibility-taking.

2.2.2 Dialogic space

As defined by the system of engagement (Martin and White 2005), dialogic space serves to reveal the writer’s manipulation of the possibilities of writer-reader dialogue, whereby the writer is able to show either solidarity or disalignment with putative readers. This system thus provides a global window through which we are able to identify the degree of negotiability/non-negotiability between writer and reader in texts. When the dialogic space is contracted, the authorial voice is given a relatively high status, leaving little or no space for negotiation for potential readers to express disagreement, challenge, or even aggression towards the given proposition; when the dialogic space is expanded, there are more possibilities for writer and reader to negotiate with each other (Table 4).

4.1.1 Evidential taxonomy

As the probabilities in UAMCT indicate (Table 5), three of the four features can be seen as characterized by significant statistical differences. Reporting is selected more frequently in specialized science texts (1011/70.80%) than in popular science texts (964/55.28%). In Belief and Inferring, there is an opposite situation: the choices in popular science texts (36/2.06% for Belief; 712/40.83% for Inferring) outnumber those in specialized science texts (14/0.98% for Belief; 388/27.1% for Inferring). The above provides a statistical basis, for identifying patterns not only in the first-order features such as Sensory, Reporting, Belief and Inferring, but also their sub-features such as Other-reporting and Self-reporting in Reporting; Modal Verb, Modal Adjective, Modal Adjunct, Prepositional Phrase, Modal Nominalization in Inferring, etc. Noteworthily here, the probability outputted in UAMCT is divided into two visions: the global and the local (O’Donnell 2013: 35). The former represents the percentage as a proportion where a featured segment occupies a total number of coded features within an overall sys-net; the latter represents the percentage as a proportion where a featured segment occupies a total number of coded features in a particular system that includes the feature (O’Donnell 2013: 35).

Under the heading of Reporting, specialized science prefers Self-reporting (168/16.62%), while popular science favors Other-reporting (963/99.90%). See Table 6.

At this point, the tendency towards Self-reporting in specialized science texts gives us a hint that the propositional information in specialized science is semioticized as the researcher’s possession – their own first-hand experience of the virus. In contrast, the statistical evidence that popular science tends more to Other-reporting shows that the proposition is more likely to be represented as a quotation by external voices, typically from specialists. The difference above can be exemplified by the different selections of information source, as shown in (2) and (3).

(2) exemplifies the use of first-person pronoun as the information source, so that in the context of Dataset 1 the information in the proposition can be construed as a statement made by the writers themselves or specialists. For the Dataset 2, the strategy shown in (3) is pervasive in borrowing specialists’ professional voices to state propositions that the writer supports, in order to enhance the warrantability of the text and ultimately to gain a wider understanding from a lay readership. As we move further into second-order feature in reporting, it is likewise observable that popular science engages more in the verbal type of Other-reporting (as shown in (3)) while specialized science prefers the non-verbal (see (4)).

From the example above, we can sense that knowledge in specialized science is construed not only through the open expression of we but also by the zero-form as expressed by the passive form of the verb with no overt agent, guiding the putative readers’ attention to some external source of information (e.g. Figure 1 as Graphics-&-Data in (4)). Popular science, in contrast, shows a comparatively strong preference for nominalization (see (5)) and according-type (see (6)) within the non-verbal type of Other-reporting.

For the writer of popular science, evidential uses, such as examples (5) and (6) together with the verbal type in (3), demonstrates a commitment to linguistic credibility. By construing it can be clean N95 masks as an evidence, the case of (5) shows the writer’s way of assigning the proposition to a Thing with factual status. It can otherwise be congruently reworded as that it can be clean N95 masks is evident. (6), in a non-verbal way, adopts an external voice, instead of authorial identity, as the information source for the proposition economic activity seems to be rebounding. These evidential usages, as a whole, appear to be dedicated to finding so-called “evidence”. As our precondition for evidentiality states, the author of the text is supposed to be responsible for every single word, phrase, sentence, or citation occurred in his/her text, but in fact this is not the usual way. What is more interesting, as shown in (5) and (6), is that the writer’s modal responsibility has been shifted in an implicit way.

As shown in Table 6, in popular science the choice of Belief is characterized by high local probability, while specialized science prefers the use of authorial voice by, for example, Self-reporting. Popular science emphasizes Belief, while specialized science attends to Self-reporting. While the writer’s own voice may be presented explicitly in both registers, it is the trends in the evidential choices that make a difference. Furthermore, Self-reporting in specialized science prefers Material and Verbal Processes, characterizing the proposition as Goal and Verbiage respectively. In contrast, Belief in popular science centers on Mental Processes that can lead potential readers to treat the proposition as one of the author’s subjective inner experiences such as imagination, consciousness, perception, etc. (Halliday and Matthiessen 2014: 251–253). See (7):

By adopting we as the information source and know as evidential marker, example (7) shapes a community between the writer and the reader as a collective Sensor and helps to construct the proposition as a mental experience that can be felt, thought of, and cognized. Understandably, the amount of such usage will be constrained, to a larger extent, in specialized science, because the conventional semiotic mode of specialized science does not allow subjective expressions to run over the whole text. The same also goes for popular science texts, yet at a comparatively lower level. Science specialization is typically valorized in terms of its discovery of nature and truth (Halliday and Martin 1993: 2–21), but popularization of science aims to recontextualize this immanent value of specialization by showing the consequence of such values and how their products are put to work in public lives (Calsamiglia 2003: 140). In this process of recontextualization, the greater attention to Belief is one of the variational features that characterizes popular science.

Within the domain of Inferring, popular science prefers modal verbs (575/80.76%), whereas specialized science favors modal adjectives (64/16.49%) and modal adjuncts (80/20.62%). See Table 7.

Such patterns correspond with Halliday’s (1985: 94–96, 2004 [1998a]: 43, 2004 [1998b]: 59–73) statements about differentiation in Mode, one of the three variables of situational context. As a text becomes more stylized, more technical and formal, the frequency of nominalization increases by re-construing more processes (i.e. verbs) into products/things (i.e. nouns). Conversely, as a text is characterized as more common-sense and informal, the frequency of verbalization goes up by transforming more human experiences into “doings” and “happenings” (i.e. verbs). In this sense, we argue that according to our comparison, specialized science is concerned with both nominalization and verbalization, but popular science places verbalization at more of a focal point. The pattern discussed above is also exemplified in (8), (9) and (10) below:

The use of a modal verb is the most congruent form for evaluating the certainty of a proposition. In (10), the writer valorizes the credibility of the proposition people have Covid-19 by a modal verb of lower certainty may. In this case, the authorial voice is masked by not referring to the author him/herself, for example, using personal pronouns such as I, we, etc. May here functions as a verbal operator realizing the Finite in the Mood structure, with the aim of maintaining the certainty of that proposition at a lower level and accordingly at a higher level its arguability value. Also serving the modal functions of verbalization is the modal adjunct, as shown in (9). In the syntagm, probably functions as modal adjunct within Mood structure, appraising the given proposition with a median value. The choice of probably implies that the possibility that the external validation datasets are not representative of the target population is neutral, leaving room for either extreme, i.e. positive or negative. Unlike (10) and (9), in (8) the evidential marker notable is not directly part of the Mood structure, but rather functions as the Head of a Complement in the Residue, attributing a higher probability both to the dummy subject (i.e. it) and the real subject (i.e. the whole proposition healthcare workers as well as close contacts of previously confirmed patients were likely to have a good outcome […]). In the Transitivity structure, a Relational Process (the attributive intensive type in particular) lies between the evidential marker notable and the given proposition. In other words, if the proposition is metaphorically nominalized as a Thing in the nominal group, the evidential marker notable can naturally function as Epithet modifying the values and qualities of the Thing.

4.1.2 Information source

The raw counts of all features in information source are 3046. And they are distributed in terms of different preferences in two registers (Table 8).

Among the three first-order features in information source, we see that the feature Human is the most frequent in the popular science texts (1348/83.06%), while Non-human (795/55.87%) and Unknown (32/2.25%) are more likely for the specialized science texts. As our focus moves towards higher delicacy into Human type, it can be seen that comparatively the specialized text’s choices are much simpler – only Author (584/97.99%) and Patient (7/1.17%) – while the popular text’s choices are multifarious: with Specialist (328/24.33%), Spokesperson (242/17.95%), Interviewee (105/7.79%), Leader (43/3.19%), and Reporter (21/1.56%). In making choices among Non-human features, the tendency towards monotony in the specialized text versus diversity in popular texts continues. The specialized texts feature a prominence of Graphics-&-Data (640/80.50%) and Current research (52/6.54%), whereas the popular texts foreground such features as Other research (44/16.18%), Country (24/8.82%), Institution (130/47.79%), Status quo (8/2.94%), Experience (12/4.41%), Virus (5/1.84%), Report (11/4.04%), and Documentation (20/7.35%).

Within specialized science texts, the interest in Non-human and Unknown is in tune with Prigogine and Stengers (1984: 6) standpoint that science, especially the natural sciences, as a successful dialogue with silent nature, often isolates humans from its object instead of bringing them closer to it, by revealing a dead, passive, and automated nature to humans. Rhetorically, it functions to construct the proposition as coming from an objective entity, with an obvious accommodation to the conventional criteria in scientific writing of clearness, objectivity, persuasiveness, and impersonality (Halliday 2004 [1997]: 181; Martin and Veel 1998).

In terms of Human source, the specialized texts pay more attention to the interaction between the scientists and their objects of study. Evidentiality is here deployed to construe propositional information either as diagnostic findings from the writers – who are also experts in this field, as shown in example (2) above – or as the representation of patients’ symptoms, conditions, reactions, etc. (see (11)).

It is obvious that know in (11) is a belief evidential (i.e. Mental Process – Cognition type – in Transitivity structure) construing the proposition they are putting those they care about most at risk of contracting the disease as a Phenomenon sensed by patients as Sensor. The similar situation also goes for the reporting evidential through which the information is reported as Goal or Verbiage assigned modal responsibility by patients (Halliday and Matthiessen 2014: 225–228, 255). This suggests the writers’ rigorous and detailed attitudes toward almost every aspect of the diagnosed patients.

In order to evaluate the material, enhance its own persuasiveness, and acknowledge alternative views (Hyland 2005a: 66–67), specialized science symbolizes the collaboration between the writers’ stance and external voices from other scholars’ findings (Miller 1979: 616). Noteworthily, in terms of Non-human sources, the specialized texts seem however to be singing the opposite tune to the norm above by their non-prominent use of Other research and the prominent use of Graphics-&-Data and Current research. As a matter of fact, this is not a deviation from the norm but a unique rhetorical device in line with the classic belief of academic writing – representation of discourse about “Truth” (Lemke 1995: 178) and heavy dependence on fact-based reasoning, dispassionate observation, and the informed reflection. The citation of Graphics-&-Data functions to construe the source of the proposition as visualized data extracted from clinical results, and further to intensify the actuality and authenticity of the information provided. The citation of Current research (e.g. our study), mainly during the transition from data to findings, is adopted to elaborate on methodology and discussion which emphasize to some extent the subjectification of certain propositions.

The ways scholars view the world are usually different from the laypeople’s commonsense ways (Halliday 2004 [1995]: 7–8). In popular science, the transition between these two viewpoints tends to entail a re-selection of information source, for example, by construing its propositional information as specialists’ findings, spokespersons’ announcements, patients’ symptoms, interviewees’ on-site experiences, etc. For selections in Human and Non-human sources, two quantitative rankings can be listed to show that the choices in the popular texts are significantly more prominent than in the specialized texts: (i) in terms of Human, Specialist (328/24.33%) > Spokesperson (242/17.95%) > Interviewee (105/7.79%) > Leadership (43/3.19%) > Reporter (21/1.56%); (ii) in terms of Non-human, Institution (130/47.79%) > Other research (44/16.18%) > Country (24/8.82%) > Documentation (20/7.35%) > Experience (12/4.41%) ≈ Report (11/4.04%) > Status quo (8/2.94%).

In terms of evidentiality, whether the popularization of science is successful seems to depend on its writers’ strategic selections in both Human and Non-human options. Our data show that the specification of information source in popular science text is a process of value assignment to the given proposition. In the Human type, the proposition is most often construed as: (i) the voice of expertise that reinforces the professionalism and authoritativeness of its content, i.e. Expert; (ii) the collective stance of a group of people who share an institutional interest, i.e. Spokesperson; (iii) the voices of ordinary individuals that highlight their concerns about the experiences and opinions of members of society, i.e. Interviewee. Likewise, its Non-human counterparts also play a constructive role in the given propositions. The top priority is assigned to a construal identifying the propositional information as: (i) the outcome of collective decision-making in medical institutions, i.e. Institution; (ii) other medical scientists’ research findings, i.e. Other research; and (iii) reports on the pandemic situation in particular countries, i.e. Country.

4.2.1 Modal responsibility

“Modal responsibility” is a semantic concept that highlights the writer’s position along a scale of how overtly s/he expresses his/her attitude towards the credibility of the propositions provided (Thompson 2004: 69–72). Statistical evidence for differences between the two registers is essential for explicating the different strategies of realizing modal responsibility. Simply in terms of orientation and value, the difference is already clear to see: in value, the specialized science texts favor High degree (377/48.90%) while the popular science texts prefer Low degree (974/68.88%); in orientation, the specialized texts favor Subjective (434/56.29%) and Explicit (221/28.66%), whereas the popular texts favor Objective (880/62.23%), especially The Most Objective (796/56.29%). However, the fact that this system involves two simultaneous subsystems with a shared entry condition (Halliday 1966; Tucker 1998: 40, 99–113; Eggins 2004: 195–197) necessitates further observation of the results of co-selections (Table 9).

Table 9 above demonstrates that the two registers differ at each point along the cline of objectivation. By foregrounding the different preferences in popular science and specialized science for cross-classified features in modalization, our comparative interpretation has been organized along the cline of “the extent to which the writer openly accepts responsibility for the subjective assessments being expressed” (Thompson 2004: 71).

Along this cline, specialized science text favors each value – Low value (incl. Implicit Subjective), Median value (incl. Implicit Objective, Explicit Objective), and High value (incl. Explicit Subjective, Implicit Objective, and The Most Objective). With Explicit Subjective, the proposition is construed more often as an assertive and proclamatory statement for which the specialized writer as information source is explicitly responsible. The writer also frequently uses the low-value Implicit Subjective frequently to shift responsibility, building an alignment with alternative stances and leaving space for further dialogue and negotiation. In Objective domains, the value returns to Median and High: by the choice of Implicit Objective and Explicit Objective, the concealed identity of authorship evaluates the propositions as comparatively reliable, credible, and warrantable, without taking the risk of revealing their own voices; at the highest level of objectivation (i.e. The Most Objective), the proposition is construed as information either from outside sources or from the findings of current research. At the same time, evidentials for valorizing the factual status of information help to add high certainty and reliability to propositions. There is a tendency towards taking modal responsibility in specialized science texts: as the position moves further toward the objective end along the cline, more High value choices are made.

Specialized science texts, as a channel for communicating the authoritativeness of science, regard COVID-19 as not purely an academic issue but as a material threat that endangers all humankind. If most propositions in texts are construed as uncertain and unknown, the power of science will be overshadowed, and this is likely to spread the global panic. To avoid these possibilities, most propositions given in relevant research are construed as certain and assured, for the most part leaving the uncertain and the unassured unsaid. This corresponds to our statistical evidence that propositions deriving from academic community voices tend to be valorized as high, and in fulfilling this need, evidentiality plays an important role.

The popular texts show a different weighting to the specialized texts. In general, they tend to highlight a Low value of Explicit Subjective, Implicit Objective, Explicit Objective, and The Most Objective and a Median value of Implicit Subjective. By the choice of Explicit Subjective, propositions are frequently construed as negotiable and discussable objects overtly originating from the popularizer’s subjectivity. By making subjectivity implicit, the value increases to Median, underlining Hyland’s (2005a: 99) conceptualization of “newsworthiness” – news value of propositions without their certainty or uncertainty being overstated. In the domains of Objectivity, including Implicit Objective, Explicit Objective, and The Most Objective, propositions are consistently valorized as Low. To wrap up, the popularizer takes less modal responsibility, by contrast with the specialist.

Unlike the specialized texts that focus on the whole procedure of research including context, methods, discussion, findings, etc., the popularizer deals more with disseminating rather than pondering on the research findings. Since one of its keys is “entertainment” (Hyland 2009: 154), popular science functions to communicate scientific information about COVID-19 to a wider range of audiences at a more easily accessible level. As a linguistic reflection of the growing impact of science on the lives of the general public, it aims to stimulate lay readers’ interest in science and is willing to embrace a wide range of controversies and debates on science-related topics. In such dialogic circumstances, propositions are naturally construed as negotiable and open-ended. The reality, actuality, and truthfulness included in these propositions can bear any form of potential examination, revision, and update.

4.2.2 Dialogic space

That evidentiality functions to manipulate the dialogic space requires relevant statistical evidence. To this end, UAMCT allows us to automate a data output of the coded features in both datasets (Table 10). Due to the statistical insignificance of the results for Acknowledgement and Distancing, the data for Attribution in Table 10 below will not be specified as to its sub-features. Comparing the two datasets at first-order delicacy, specialized science texts favor dialogic expansion (355/44.60%) while popular science texts prefer dialogic contraction (1118/77.37%). When focusing on the resource of dialogic expansion, for specialized science texts it is foregrounded in Entertaining (326/73.92%), whereas for popular science texts it is foregrounded in Attribution (772/69.05%). When we examine the resources of Contraction, popular science texts show a tendency to Concurrence (259/79.20%), while specialized science texts lean to Endorsement (125/35.21%) and Pronouncement (110/30.99%).

In specialized science texts, the overall tendency of evidential usage towards dialogic expansion implies the specialists’ strong inclination to create an image of solidarity and thus make allowance for positions that are dialogically alternative to the authorial position. In doing so, most authorial positions are stated as one possibility among a range of potential stances available to putative readers. From the resource of dialogic expansion, the specialists choose Entertaining to state that the possibility of alternative positions co-exists with theirs. Such a usage functions to lower the authority of authorial voice in expressing propositions in the specialized texts. Usually, the author’s voices are silenced, and their implicitness is used to advocate dialogic inclusiveness where their voices or the other alternatives are treated only as one of the possible choices. Conventionally, interpersonal rhetoric in the specialized science texts is never characterized as peremptory, dogmatical or arbitrary but as inclusive, expansive, and even comprehensive.

The specialized science texts also tend to contract the dialogic scope, though their expansive choices are more prominent. Dialogic contraction requires Endorsement to construe the proposition as other researchers’ findings, functioning not only to conceal their own attitudes and responsibilities but to maintain their position as authority in an only implicit way. In a “non-self” way, the validity, facticity, correctness and sometimes even undeniability of their propositions are maximized without any risk of exposing their own voices. In addition, Pronouncement, as a dialogically contractive resource that explicitly intensifies, emphasizes, and interpolates the authorial voice, is also selected to clarify the degree to which the factual status of proposition is highlighted and authorial subjectivity engaged. In this sense, the evidentials that function to realize Pronouncement are adopted to contract the dialogic space, but still leave room for authorship to be expressed in a covert way by masking his/her subjectivity.

On the other hand, the popular science texts’ preference for dialogic contraction suggests their aim of establishing an authoritative identity vis-à-vis lay readers. Most of their evidential choices function to magnify the authorial voice, in order to keep off, limit, and even challenge alternatives. In so doing, the popularizer’s position of power over lay people can be stabilized. By using Concurrence, propositional information is more often construed as an assured consensus and sometimes even as a “promise”. Its validity, tenability, and reliability can thus be construed as a multilateral recognition. In this sense, contracting the dialogic scope signifies a focus solely on what has been reported in the proposition to build an alignment solely with positive evaluations such as acceptance, acknowledgement, agreement, etc. that are shared by author and potential readers.

In realizing dialogic expansion, Attribution is adopted to engage in a potential negotiation between the authorial voice and the alternatives. To quote external voices as information source, mostly Specialist, Spokesperson, or Interviewee, and to adopt the neutral-value evidentials, mostly say, together function to shift the popularizer’s responsibility and leave their own positioning unsaid.